Sample records for household consumption profiles from the National Library of Energy Beta (NLEBeta)

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. . Vehicle Fuel Efficiency and Consumption Fuel consumption is estimated from RTECS data on the vehicle stock (Chapter 2) and miles traveled (Chapter 3), in combination with vehicle fuel efficiency ratings, adjusted to account for individual driving circumstances. The first two sections of this chapter present estimates of household vehicle fuel efficiency and household fuel consumption calculated from these fuel efficiency estimates. These sections also discuss variations in fuel efficiency and consumption based on differences in household and vehicle characteristics. The third section presents EIA estimates of the potential savings from replacing the oldest (and least fuel-efficient) household vehicles with new (and more fuel-efficient) vehicles. The final section of this chapter focuses on households receiving (or eligible to receive) supplemental income under

1 Asset Pricing with Countercyclical HouseholdConsumption Risk George M. Constantinides that shocks to householdconsumption growth are negatively skewed, persistent, and countercyclical and play that drives the conditional cross-sectional moments of householdconsumption growth. The estimated model

3. 3. Vehicle Miles Traveled This chapter presents information on household vehicle usage, as measured by the number of vehicle miles traveled (VMT). VMT is one of the two most important components used in estimating household vehicle fuel consumption. (The other, fuel efficiency, is discussed in Chapter 4). In addition, this chapter examines differences in driving behavior based on the characteristics of the household and the type of vehicle driven. Trends in household driving patterns are also examined using additional information from the Department of Transportation's Nationwide Personal Transportation Survey (NPTS). Household VMT is a measure of the demand for personal transportation. Demand for transportation may be viewed from either an economic or a social perspective. From the economic point-of-view, the use of a household vehicle represents the consumption of one

Household Vehicles Energy Consumption 1994 reports on the results of the 1994 Residential Transportation Energy Consumption Survey (RTECS). The RTECS is a national sample survey that has been conducted every 3 years since 1985. For the 1994 survey, more than 3,000 households that own or use some 6,000 vehicles provided information to describe vehicle stock, vehicle-miles traveled, energy end-use consumption, and energy expenditures for personal vehicles. The survey results represent the characteristics of the 84.9 million households that used or had access to vehicles in 1994 nationwide. (An additional 12 million households neither owned or had access to vehicles during the survey year.) To be included in then RTECS survey, vehicles must be either owned or used by household members on a regular basis for personal transportation, or owned by a company rather than a household, but kept at home, regularly available for the use of household members. Most vehicles included in the RTECS are classified as {open_quotes}light-duty vehicles{close_quotes} (weighing less than 8,500 pounds). However, the RTECS also includes a very small number of {open_quotes}other{close_quotes} vehicles, such as motor homes and larger trucks that are available for personal use.

The purpose of this report is to provide information on the use of energy in residential vehicles in the 50 States and the District of Columbia. Included are data about: the number and type of vehicles in the residential sector, the characteristics of those vehicles, the total annual Vehicle Miles Traveled (VMT), the per household and per vehicle VMT, the vehicle fuel consumption and expenditures, and vehicle fuel efficiencies. The data for this report are based on the household telephone interviews from the 1991 RTECS, conducted during 1991 and early 1992. The 1991 RTECS represents 94.6 million households, of which 84.6 million own or have access to 151.2 million household motor vehicles in the 50 States and the District of Columbia.

Detailed Detailed Tables The following tables present detailed characteristics of vehicles in the residential sector. Data are from the 1991 Residential Transportation Energy Consumption Survey. The "Glossary" contains the definitions of terms used in the tables. Table Organization The "Detailed Tables" section consists of three types of tables: (1) Tables of totals such as number of vehicle miles traveled (VMT) or gallons consumed; (2) Tables of per household statistics such as VMT per household; and (3) Tables of per vehicle statistics such as vehicle fuel consumption per vehicle. The tables have been grouped together by specific topics such as model year data, or family income data to facilitate finding related information. The Quick-Reference Guide to the detailed tables indicates major topics of each table. Row and Column Factors These tables present estimates

1. 1. Introduction The purpose of this report is to provide information on the use of energy in residential vehicles in the 50 States and the District of Columbia. Included are data about: the number and type of vehicles in the residential sector, the characteristics of those vehicles, the total annual Vehicle Miles Traveled (VMT), the per household and per vehicle VMT, the vehicle fuel consumption and expenditures, and vehicle fuel efficiencies. The Energy Information Administration (EIA) is mandated by Congress to collect, analyze, and disseminate impartial, comprehensive data about energy--how much is produced, who uses it, and the purposes for which it is used. To comply with this mandate, EIA collects energy data from a variety of sources covering a range of topics 1 . Background The data for this report are based on the household telephone interviews from the 1991 RTECS, conducted

. . Trends in Household Vehicle Stock The 1991 RTECS counted more than 150 million vehicles in use by U.S. households. This chapter examines recent trends in the vehicle stock, as measured by the RTECS and other reputable vehicle surveys. It also provides some details on the type and model year of the household vehicle stock, and identifies regional differences in vehicle stock. Because vehicles are continuously being bought and sold, this chapter also reports findings relating to turnover of the vehicle stock in 1991. Finally, it examines the average vehicle stock in 1991 (which takes into account the acquisition and disposal of household vehicles over the course of the year) and identifies variations in the average number of household vehicles based on differences in household characteristics. Number of Household Vehicles Over the past 8 years, the stock of household vehicles has

Aggregate Aggregate Ratio: See Mean and Ratio Estimate. AMPD: Average miles driven per day. See Appendix B, "Estimation Methodologies." Annual Vehicle Miles Traveled: See Vehicle Miles Traveled. Automobile: Includes standard passenger car, 2-seater car and station wagons; excludes passenger vans, cargo vans, motor homes, pickup trucks, and jeeps or similar vehicles. See Vehicle. Average Household Energy Expenditures: A ratio estimate defined as the total household energy expenditures for all RTECS households divided by the total number of households. See Ratio Estimate, and Combined Household Energy Expenditures. Average Number of Vehicles per Household: The average number of vehicles used by a household for personal transportation during 1991. For this report, the average number of vehicles per household is computed as the ratio of the total number of vehicles to the

This presents information about household end-use consumption of energy and expenditures for that energy. These data were collected in the 1993 Residential Energy Consumption Survey; more than 7,000 households were surveyed for information on their housing units, energy consumption and expenditures, stock of energy-consuming appliances, and energy-related behavior. The information represents all households nationwide (97 million). Key findings: National residential energy consumption was 10.0 quadrillion Btu in 1993, a 9% increase over 1990. Weather has a significant effect on energy consumption. Consumption of electricity for appliances is increasing. Houses that use electricity for space heating have lower overall energy expenditures than households that heat with other fuels. RECS collected data for the 4 most populous states: CA, FL, NY, TX.

C C Quality of the Data Appendix C Quality of the Data Introduction This appendix discusses several issues relating to the quality of the Residential Transportation Energy Consumption Survey (RTECS) data and to the interpretation of conclusions based on these data. The first section discusses under- coverage of the vehicle stock in the residential sector. The second section discusses the effects of using July 1991 as a time reference for the survey. The remainder of this appendix discusses the treatment of sampling and nonsampling errors in the RTECS, the quality of specific data items such as the Vehicle Identification Number (VIN) and fuel prices, and poststratification procedures used in the 1991 RTECS. The quality of the data collection and the processing of the data affects the accuracy of estimates based on survey data. All the statistics published in this report such as total

Using monthly data from the Japanese Family Income and Expenditure Survey, we examine the impact of retirement on householdconsumption. We find little evidence of an immediate change in consumption at retirement, on average, in Japan. However, we find a decrease in consumption at retirement for low income households that is concentrated in food and work-related consumption. The availability of substantial retirement bonuses to a large share of Japanese retirees may help smooth consumption at retirement. We find that those households that are more likely to receive such bonuses experience a short-run consumption increase at retirement. However, among households that are less likely to receive a retirement bonus, we find that consumption decreases at retirement.

The need for households in rich countries to develop more sustainable consumption patterns is high on the political agenda. An increased awareness of environmental issues among the general public is often presented as an important prerequisite for this change. This article describes how the study team compared the ecological footprints of ''green'' and ''ordinary'' households. These footprint calculations are based on a number of consumption categories that have severe environmental consequences, such as energy and material use in the home, and transport. The comparison is based on a survey of 404 households in the city of Stavanger, where 66 respondents were members of the Environmental Home Guard in Norway. The analysis suggests that, even if the green households have a smaller ecological footprint per household member, this is not caused by their participation in the Home Guard. It merely reflects the fact that green households are larger than ordinary households.

This thesis studies two strategies that households may use to keep their consumption smooth in the face of fluctuations in income and expenses: credit (borrowing and savings) and insurance (state contingent transfers between ...

Abstract The share of the residential sector currently accounts for about 25% of the national electricity consumption in Turkey. Due to increase in household income levels and decrease in the costs of appliances; significant increases in appliance ownerships and residential electricity consumption levels have been observed in recent years. Most domestic appliances continue consuming electricity when they are not performing their primary functions, i.e. at standby mode, which can constitute up 15% of the total household electricity consumption in some countries. Although the demand in Turkish residential electricity consumption is increasing, there are limited studies on the components of the residential electricity consumption and no studies specifically examining the extent and effects of standby electricity consumption using a surveying/measurement methodology. Thus, determining the share of standby electricity consumption in total home electricity use and the ways of reducing it are important issues in residential energy conservation strategies. In this study, surveys and standby power measurements are conducted at 260 households in Ankara, Turkey, to determine the amount, share, and saving potentials of the standby electricity consumption of Turkish homes. The survey is designed to gather information on the appliance properties, lights, electricity consumption behavior, economic and demographics of the occupants, and electricity bills. A total of 1746 appliances with standby power are measured in the surveyed homes. Using the survey and standby power measurements data, the standby, active, and lighting end-use electricity consumptions of the surveyed homes are determined. The average Turkish household standby power and standby electricity consumption are estimated as 22 W and 95 kW h/yr, respectively. It was also found that the standby electricity consumption constitutes 4% of the total electricity consumption in Turkish homes. Two scenarios are then applied to the surveyed homes to determine the potentials in reducing standby electricity consumption of the households.

Few models attempt to assess and project household energy consumption and expenditure by taking into account differential household choices correlated with such variables as race, ethnicity, income, and geographic location. The Minority Energy Assessment Model (MEAM), developed by Argonne National Laboratory (ANL) for the US Department of Energy (DOE), provides a framework to forecast the energy consumption and expenditure of majority, black, Hispanic, poor, and nonpoor households. Among other variables, household energy demand for each of these population groups in MEAM is affected by housing factors (such as home age, home ownership, home type, type of heating fuel, and installed central air conditioning unit), demographic factors (such as household members and urban/rural location), and climate factors (such as heating degree days and cooling degree days). The welfare implications of the revealed consumption patterns by households are also forecast. The paper provides an overview of the model methodology and its application in projecting household energy consumption under alternative energy scenarios developed by Data Resources, Inc., (DRI).

Sample records for household consumption profiles from the National Library of Energy Beta (NLEBeta)

Note: This page contains sample records for the topic "household consumption profiles" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.

Few models attempt to assess and project household energy consumption and expenditure by taking into account differential household choices correlated with such variables as race, ethnicity, income, and geographic location. The Minority Energy Assessment Model (MEAM), developed by Argonne National Laboratory (ANL) for the US Department of Energy (DOE), provides a framework to forecast the energy consumption and expenditure of majority, black, Hispanic, poor, and nonpoor households. Among other variables, household energy demand for each of these population groups in MEAM is affected by housing factors (such as home age, home ownership, home type, type of heating fuel, and installed central air conditioning unit), demographic factors (such as household members and urban/rural location), and climate factors (such as heating degree days and cooling degree days). The welfare implications of the revealed consumption patterns by households are also forecast. The paper provides an overview of the model methodology and its application in projecting household energy consumption under alternative energy scenarios developed by Data Resources, Inc., (DRI).

Energy Consumption of Refrigerators in Ghana - Outcomes of Household Energy Consumption of Refrigerators in Ghana - Outcomes of Household Surveys Speaker(s): Essel Ben Hagan Date: July 12, 2007 - 12:00pm Location: 90-3122 Seminar Host/Point of Contact: Robert Van Buskirk Galen Barbose As part of activities to develop refrigerator efficiency standards regulations in Ghana, a national survey on the energy consumption of refrigerators and refrigerator-freezers has been conducted. The survey covered 1000 households in urban, peri-urban and rural communities in various parts of the country. The survey found that, on average, refrigerators and refrigerator-freezers in Ghana use almost three times what is allowed by minimum efficiency standards in the U.S., and a few refrigerators had energy use at levels almost ten times the U.S.

Total United States energy consumption in homes has remained relatively stable for many years as increased energy efficiency has offset the increase in the number and average size of housing units, according to the newly released data from the Residential Energy Consumption Survey (RECS). The average household consumed 90 million British thermal units (Btu) in 2009 based on RECS. This continues the downward trend in average residential energy consumption of the last 30 years. Despite increases in the number and the average size of homes plus increased use of electronics, improvements in efficiency for space heating, air conditioning, and major appliances have all led to decreased consumption per household. Newer homes also tend to feature better insulation and other characteristics, such as double-pane windows, that improve the building envelope.

This study concentrates on the analysis of energy consumption, expenditure on oil and LPG use in cars and aims to examine the elasticity effect of various types of oil consumption. By using the Deaton's analysis framework, the cross-sectional data of Thai households economic survey 2009 were used. By defining energy goods in the scope of automobile fuel, the results reflect the low importance of high-quality automobile fuel on all income level households. Thai households tend to vary the quality rather than the quantity of thermal energy. All income groups have a tendency to switch to lower quality fuel. Middle and high-middle households (Q3 and Q4) are the income groups with the greatest tendency to switch to lower-quality fuel when a surge in the price of oil price occurs. The poorest households (Q1) are normally insensitive to a change of energy expenditure in terms of quality and quantity. This finding illustrates the LPG price subsidy policy favours middle and high-middle income households. The price elasticity of energy quantity demand is negative in all income levels. High to middle income families are the most sensitive to changes in the price of energy.

Introduction This appendix discusses several issues relating to the quality of the Residential Transportation Energy Consumption Survey (RTECS) data and to the interpretation of conclusions based on these data. The first section discusses undercoverage of the vehicle stock in the residential sector. The second section discusses the effects of using July 1994 as a time reference for the survey. The remainder of this appendix discusses the treatment of sampling and nonsampling errors in the RTECS, the quality of specific data items such as the Vehicle Identification Number (VIN) and fuel prices, and poststratification procedures used in the 1994 RTECS. The quality of the data collection and the processing of the data affects the accuracy of estimates based on survey data. All the statistics

This article analyses the relationship between environmental attitudes and energy use in the home and for transport by Norwegian households. Quantitative surveys were used to find statistical correlations, and qualitative analyses to reveal mechanisms that influence the ability to behave in an environmentally friendly way. Three theses about attitudes, mechanisms and householdconsumption are presented. Firstly, a desire to project an environmentally friendly image has little influence on energy use in the home and for transport. Secondly, a sense of powerlessness prevents people from translating positive environmental attitudes into low energy use in the home and for everyday transport. Thirdly, a desire to self-indulge prevents people from translating positive environmental attitudes into low energy use for long distance leisure travel. These results have important implications for environmental policy. Public information and awareness campaigns can give consumers information on how to behave in an environmentally responsible way, but tend only to influence categories of consumption with little environmental impact. Structural change can be used to mitigate the effect of the sense of powerlessness and encourage environmentally friendly behaviour, but the desire to self-indulge is much more difficult to deal with.

In this paper a descriptive analysis of the relationship between energy consumption, patterns of energy use, and housing stock variables is presented. The purpose of the analysis is to uncover evidence of variations in energy consumption and expenditures, and patterns of energy use between majority households (defines as households with neither a black nor Hispanic head of household), black households (defined as households with a black head of household), and Hispanic households (defined as households with a Hispanic head of household) between 1980 (time of the first DOE/EIA Residential Energy Consumption Survey, 1982a) and 1987 (time of the last DOE/EIA Residential Energy Consumption Survey, 1989a). The analysis is three-dimensional: energy consumption and expenditures are presented by time (1980 to 1987), housing vintage, and housing type. A comparative analysis of changes in energy variables for the three population groups -- majority, black, and Hispanic -- within and between specific housing stock categories is presented.

In this paper a descriptive analysis of the relationship between energy consumption, patterns of energy use, and housing stock variables is presented. The purpose of the analysis is to uncover evidence of variations in energy consumption and expenditures, and patterns of energy use between majority households (defines as households with neither a black nor Hispanic head of household), black households (defined as households with a black head of household), and Hispanic households (defined as households with a Hispanic head of household) between 1980 (time of the first DOE/EIA Residential Energy Consumption Survey, 1982a) and 1987 (time of the last DOE/EIA Residential Energy Consumption Survey, 1989a). The analysis is three-dimensional: energy consumption and expenditures are presented by time (1980 to 1987), housing vintage, and housing type. A comparative analysis of changes in energy variables for the three population groups -- majority, black, and Hispanic -- within and between specific housing stock categories is presented.

Energy use in the Japanese residential sector has more than doubled (on a per-household basis) during the post-war period. Important factors contributing to the increase include changes in the types of housing built, heating, cooling, water-heating equipment, and other appliances. In this paper, the developments of household equipment and living conditions in Japan are described, from their 1950s state to the present. Trends in energy consumption by fuel types and end uses are reviewed over the same period. The past trends are combined with expectations for future developments in household equipment and quality, as well as with international comparisons of household-energy use, to predict further increases in household-energy consumption. The results indicate the importance of a renewed emphasis on energy efficiency in the residential sector.

appropriate strategies of giving households' effective feedback on their energy consumption. This study, Energy efficiency. I. INTRODUCTION HE energy consumption of households in buildings attracts a lot in the housing sector. Energy consumption in buildings accounts for 39% of Sweden's total final energy

Abstract Twenty percent of the total energy consumption in the Netherlands comes from household electricity consumption. This comes from household electric appliances whose number has grown in recent years. The paper explores the effect of smart meter introduction, appliance efficiency and consumer behaviour on reducing electricity consumption in the Netherlands. It does so by combining two perspectives: a sociotechnical approach and a bottom up simulation approach. The range of scenarios explored through simulation in the paper provides an understanding of the interplay between efficiency, smart meter diffusion and consumer behaviour. The results show their effect on electricity consumption and suggest that further effort is required to control and reduce it. Insights from the paper suggest that future studies should disaggregate with respect to a number of factors.

In this paper, I analyze the causes of the prolonged slowdown of the Japanese economy in the 1990s and find that the stagnation of investment, especially private fixed investment, was the primary culprit. I then investigate the causes of the stagnation of householdconsumption during the 1990s and find that the stagnation of household disposable income, the decline in household wealth, and increased uncertainty about the future are among the contributing factors. Finally, I consider whether demand side factors or supply side factors were more important as causes of the prolonged slowdown of the Japanese economy in the 1990s and conclude that the former (especially misguided government policies) were probably more important.

The Iraqi invasion of the Kingdom of Kuwait on August 2, 1990, and the subsequent war between Iraq and an international alliance led by the United States triggered first immediate and then fluctuating world petroleum prices. Increases in petroleum prices and in U.S. petroleum imports resulted in increases in the petroleum prices paid by U.S. residential, commercial, and industrial consumers. The result was an immediate price shock that reverberated throughout the U.S. economy. The differential impact of these price increases and fluctuations on poor and minority households raised immediate, significant, and potentially long-term research, policy, and management issues for a variety of federal, state, and local government agencies, including the U.S. Department of Energy (DOE). Among these issues are (1) the measurement of variations in the impact of petroleum price changes on poor, nonpoor, minority, and majority households; (2) how to use the existing policy resources and policy innovation to mitigate regressive impacts of petroleum price increases on lower-income households; and (3) how to pursue such policy mitigation through government agencies severely circumscribed by tax and expenditure limitations. Few models attempt to assess household energy consumption and energy expenditure under various alternative price scenarios and with respect to the inclusion of differential household choices correlated with such variables as race, ethnicity, income, and geographic location. This paper provides a preliminary analysis of the nature and extent of potential impacts of petroleum price changes attributable to the Persian Gulf War and its aftermath on majority, black, and Hispanic households and on overlapping poor and nonpoor households. At the time this was written, the Persian Gulf War had concluded with Iraq`s total surrender to all of the resolutions and demands of the United Nations and United States.

Sample records for household consumption profiles from the National Library of Energy Beta (NLEBeta)

Note: This page contains sample records for the topic "household consumption profiles" from the National Library of EnergyBeta (NLEBeta).
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they are not comprehensive nor are they the most current set.
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to obtain the most current and comprehensive results.

Exhausted energy consumption becomes a world-wide issue nowadays. Computing contributes a large portion of energy consumption. The concept of green computing has been popularized. Along with the rapid development of China, energy issue becomes more and ... Keywords: energy/electricity consumption, IT industry, household computers, energy efficiency, green computing

at 215 million Btu. The rate of consumption generally increased until the oil price shocks of the midChanging Trends: A Brief History of the US HouseholdConsumption of Energy, Water, Food, Beverages understand energy conservation policies, we take a brief look at the history in the US of consumption

This paper addresses the topic of energy and development through a multi-disciplinary and systemic approach that combines environmental considerations with a social understanding of consumption. The focus is on electricity usage in the home and specifically lighting and cooling. Set in the urban mega-polis of Metro Manila, the Philippines, energy consumption is first placed in its biophysical perspective: the energy sources and electricity grid are presented, in relation to the Philippines as well as the region. The research findings then explore the social and cultural drivers behind household electricity consumption, revealing in several examples the strong influence of globalization—understood here as the flow of people, remittances, images and ideas. Policy recommendations are provided, based on the research results, with concluding remarks relevant to other similar contexts.

This report presents an analysis of the relative impacts of the National Energy Strategy on majority and minority households and on nonpoor and poor households. (Minority households are defined as those headed by black or Hispanic persons; poor households are defined as those having combined household income less than or equal to 125% of the Office of Management and Budget`s poverty-income threshold.) Energy consumption and expenditures, and projected energy expenditures as a share of income, for the period 1987 to 2009 are reported. Projected consumptions of electricity and nonelectric energy over this period are also reported for each group. An analysis of how these projected values are affected under different housing growth scenarios is performed. The analysis in this report presents a preliminary set of projections generated under a set of simplifying assumptions. Future analysis will rigorously assess the sensitivity of the projected values to various changes in a number of these assumptions.

Residential energy cost is an important part of the household budget and could vary significantly across different population groups in many countries. In the United States, many studies have analyzed household fuel consumption by fuel type, including electricity, natural gas, fuel oil, and liquefied petroleum gas (LPG), and by geographic areas. Past research has also demonstrated significant variation in residential energy use across various population groups, including white, black, and Latino. However, our research shows that residential energy demand by fuel type for Latinos, the fastest growing population group, has not been explained by economic and non-economic factors in any statistical model in public domain. The purpose of this paper was to discuss energy demand and expenditure patterns for Latino and non-Latino households in the United States as a case example of analyzing residential energy consumption across different population groups in a country. The linear expenditure system model developed by Stone and Geary is the basis of the statistical model developed to explain fuel consumption and expenditures for Latino households. For comparison, the models are also developed for non-Latino, black, and non-black households. These models estimate energy consumption of and expenditures for electricity, natural gas, fuel oil, and LPG by various households at the national level. Significant variations in the patterns of these fuels consumption for Latinos and non-Latinos are highlighted. The model methodology and results of this research should be useful to energy policymakers in government and industry, researches, and academicians who are concerned with economic and energy issues related to various population groups in their country.

Using micro-level household data in the 2001 Comprehensive Survey of the Living Conditions of the People on Health and Welfare compiled by the Japanese Ministry of Health, Labor and Welfare, this paper examines how having a household member in need of long-term nursing care can result in welfare losses measured in terms of consumption. In so doing, this study evaluates the role of the public long-term care insurance scheme implemented in Japan in April 2000. The results indicate that when households include a disabled family member, householdconsumption net of long-term care costs do not decrease as much as before the introduction of long-term care insurance. Further, when compared with the surveys conducted in 1998, the adverse effects on consumption net of long-term care costs have become much weaker. These findings suggest that the introduction of social insurance in 2000 helped Japanese households to reduce the welfare losses associated with a disabled family member.

Abstract Rural household energy consumption plays an essential role in the daily life of farmers, especially in developing regions. In this paper, we present a study of household energy consumption in terms of energy sources and energy end uses, and analysis of technical and economic issues associated with the use of biomass and renewable energy and the replacement of fossil fuels. Results show that energy from biomass represents the largest share of total energy supply, and that 41.15% of total energy is consumed for home heating and cooking. The average cost of household energy is 1259 RMB ($US193.6) and this expense is no longer subsidized by the government. It takes less than one year to make a solar stove profitable and less than two years to pay back the household cost of biogas digesters. An 8 m3 digester can produce as much energy as 500–550 kg of standard coal or 940 kg of firewood, while a solar stove can generate 1.76 × 103 MJ heat each year. Moreover, it is estimated that in rural China the annual reduction of CO2 and SO2 emissions in 2020, due to the replacement of fossil fuel by biomass, will be 68.86 × 106 and 54.37 × 104 tons, respectively. Overall, the investigations and analyses have revealed that the structure of rural household energy consumption is undergoing a transformation from traditional low-efficiency biomass domination to integrated consumption of traditional and renewable energies. Renewable energy will significantly contribute to the sustainable development of rural households.

Methods, apparatus, and products are disclosed for profiling an application for power consumption during execution on a compute node that include: receiving an application for execution on a compute node; identifying a hardware power consumptionprofile for the compute node, the hardware power consumptionprofile specifying power consumption for compute node hardware during performance of various processing operations; determining a power consumptionprofile for the application in dependence upon the application and the hardware power consumptionprofile for the compute node; and reporting the power consumptionprofile for the application.

Household in-home activities and out-of-home transportation are two major sources of urban energy consumption. In light of China's rapid urbanization and income growth, changing lifestyles and consumer patterns - evident ...

Abstract This paper presents a high-resolution bottom-up model of electricity use in an average household based on fit to probability distributions of a comprehensive high-resolution household electricity use data set for detached houses in Sweden. The distributions used in this paper are the Weibull distribution and the Log-Normal distribution. These fitted distributions are analyzed in terms of relative variation estimates of electricity use and standard deviation. It is concluded that the distributions have a reasonable overall goodness of fit both in terms of electricity use and standard deviation. A Kolmogorov–Smirnov test of goodness of fit is also provided. In addition to this, the model is extended to multiple households via convolution of individual electricity use profiles. With the use of the central limit theorem this is analytically extended to the general case of a large number of households. Finally a brief comparison with other models of probability distributions is made along with a discussion regarding the model and its applicability.

Residential energy cost, an important part of the household budget, varies significantly across different population groups. In the United States, researchers have conducted many studies of household fuel consumption by fuel type -- electricity, natural gas, fuel oil, and liquefied petroleum gas (LPG) -- and by geographic areas. The results of past research have also demonstrated significant variation in residential energy use across various population groups, including white, black, and Latino. However, research shows that residential energy demand by fuel type for Latinos, the fastest-growing population group in the United States, has not been explained by economic and noneconomic factors in any available statistical model. This paper presents a discussion of energy demand and expenditure patterns for Latino and non-Latino households in the United States. The statistical model developed to explain fuel consumption and expenditures for Latino households is based on Stone and Geary`s linear expenditure system model. For comparison, the authors also developed models for energy consumption in non-Latino, black, and nonblack households. These models estimate consumption of and expenditures for electricity, natural gas, fuel oil, and LPG by various households at the national level. The study revealed significant variations in the patterns of fuel consumption for Latinos and non-Latinos. The model methodology and results of this research should be useful to energy policymakers in government and industry, researchers, and academicians who are concerned with economic and energy issues related to various population groups.

In 2012, the residential sector accounted for 21% of total primary energy consumption and about 20% of carbon dioxide emissions in the United States (computed from EIA 2013). Because of the impacts of residential sector energy use on the environment and the economy, this study was undertaken to help provide a better understanding of the factors affecting energy consumption in this sector. The analysis is based on the U.S. Energy Information Administration's (EIA) residential energy consumption surveys (RECS) 1980-2009.

refers to these latent goods as transformed goods or T-goods. Leading researchers have explored this technique of incorporating characteristics. In this study, we revisit this technique by trying to uncover the basic wants behind the demand for gas..., distillate fuel oil, and the liquefied petroleum gases (LPG) by US households. To give some examples, electricity may be used for many basic wants such as lighting, cooking, and cooling. Similarly, without being exhaustive, gas may be used for heating...

With decades of economic growth and socio-economic transformation, China's residential sector has seen rapid expansion in energy consumption, and is now the second largest energy consuming sector in the country. Faced with ...

Key Assumptions Key Assumptions The historical input data used to develop the HEM version for the AEO2000 consists of recent household survey responses, aggregated to the desired level of detail. Two surveys performed by the Energy Information Administration are included in the AEO2000 HEM database, and together these input data are used to develop a set of baseline householdconsumptionprofiles for the direct fuel expenditure analysis. These surveys are the 1997 Residential Energy Consumption Survey (RECS) and the 1991 Residential Transportation Energy Consumption Survey (RTECS). HEM uses the consumption forecast by NEMS for the residential and transportation sectors as inputs to the disaggregation algorithm that results in the direct fuel expenditure analysis. Household end-use and personal transportation service consumption are obtained by HEM from the NEMS Residential and Transportation Demand Modules. Household disposable income is adjusted with forecasts of total disposable income from the NEMS Macroeconomic Activity Module.

In this paper we explore a fundamental characteristic of Ambient Persuasive Technology: Can it persuade the user without receiving the user's conscious attention? In a task consisting of 90 trials, participants had to indicate which of three household ... Keywords: ambient persuasive technology, energy conservation behavior, human-technology interaction, persuasion, social feedback, subliminal feedback

Completed Copy in PDF Format Completed Copy in PDF Format Related Links Annual Energy Outlook2001 Supplemental Data to the AEO2001 NEMS Conference To Forecasting Home Page EIA Homepage Household Expenditures Module Key Assumptions The historical input data used to develop the HEM version for the AEO2001 consists of recent household survey responses, aggregated to the desired level of detail. Two surveys performed by the Energy Information Administration are included in the AEO2001 HEM database, and together these input data are used to develop a set of baseline householdconsumptionprofiles for the direct fuel expenditure analysis. These surveys are the 1997 Residential Energy Consumption Survey (RECS) and the 1991 Residential Transportation Energy Consumption Survey (RTECS). HEM uses the consumption forecast by NEMS for the residential and

Sample records for household consumption profiles from the National Library of Energy Beta (NLEBeta)

Note: This page contains sample records for the topic "household consumption profiles" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.

4 4 Transportation logo printer-friendly version logo for Portable Document Format file Household Vehicles Energy Consumption 1994 August 1997 Release Next Update: EIA has discontinued this series. Based on the 1994 Residential Transportation Energy Consumption Survey conducted by the Energy Information Administration (EIA) - survey series has been discontinued Only light-duty vehicles and recreational vehicles are included in this report. EIA has excluded motorcycles, mopeds, large trucks, and buses. Household Vehicles Energy Consumption 1994 reports on the results of the 1994 Residential Transportation Energy Consumption Survey (RTECS). The RTECS is a national sample survey that has been conducted every 3 years since 1985. For the 1994 survey, more than 3,000 households that own or use

The Iraqi invasion of Kuwait and the subsequent war between Iraq and an international alliance led by the United States triggered immediate increases in world oil prices. Increases in world petroleum prices and in US petroleum imports resulted in higher petroleum prices for US customers. In this report, the effects of the Persian Gulf War and its aftermath are used to demonstrate the potential impacts of petroleum price changes on majority, black, and Hispanic households, as well as on poor and nonpoor households. The analysis is done by using the Minority Energy Assessment Model developed by Argonne National Laboratory for the US Department of Energy (DOE). The differential impacts of these price increases and fluctuations on poor and minority households raise significant issues for a variety of government agencies, including DOE. Although the Persian Gulf crisis is now over and world oil prices have returned to their prewar levels, the differential impacts of rising energy prices on poor and minority households as a result of any future crisis in the world oil market remains a significant long-term issue.

A large variety of construction patterns can be found in public-housing programs for lower-mid income families in Santa Rosa, a fast growing city located in a temperate area of central Argentina. Very little attention has been paid to the energy assessment of different patterns that are needed to prescribe energy-saving guidelines for improving the energy performance of housing plans. The objective of this work was to describe the energy profile and understand the energy behaviour of public housing programs which differ in their construction patterns. The annual and seasonal energy behaviour of public and non-public residential dwellings was compared in terms of electricity and gas consumption. A similar comparison between remodelled and non-remodelled dwellings was performed within the public-dwellings sample. Results showed that public and non-public dwellings did not differ in terms of electricity consumption, but they differed greatly in terms of gas consumption. Non-public dwellings, which are larger and heterogeneous, demand more gas for heating during the winter. No difference in annual energy consumption was found in the comparison of remodelled and non-remodelled public dwellings. However, they differ in electricity consumption patterns during the critical winter season: the lower winter consumption of remodelled dwellings could be partially explained by a construction change aimed at lowering the expensive consumption of electricity. In spite of the fact that the energy behaviour of public dwellings seems to be seasonal, dependent upon more than design factors alone, a significant energy saving can be obtained by introducing well-known design technologies.

Abstract Currently there is a strong policy commitment in European Union (EU) and Organisation for Economic Co-operation and Development (OECD) countries to increase the energy efficiency of residential buildings, and it is widely assumed that this will naturally and automatically reduce domestic energy consumption. However, other factors such as fuel prices, wages, attitudes and lifestyles also influence energy consumption. This paper calculates broad-brush rebound effects based on changes in energy efficiency and energy consumption in each of the 28 EU countries plus Norway, for the years 2000–2011. In doing so, it tests how well the assumption of energy efficiency leading to energy reduction stands up to scrutiny in these lands. It uses the EU’s Odyssee database for efficiency and consumption figures and a commonly employed econometric definition of the rebound effect as an energy-efficiency elasticity. Most older EU lands show rebound effects in the expected range of 0–50%. However, the range for newer EU countries is 100–550%, suggesting that energy efficiency increases are not a good predictor of energy consumption. A more in-depth look at one country, Germany, suggests these results underestimate the rebound effect significantly. This also identifies research needs for specific energy consumption determinants in each country, to find more precisely what is driving consumption levels.

Efforts to mitigate climate threats should not exclude the household as the household is a major driver of greenhouse gas (GHG) emissions through its consumption...2) emissions from kerosene combustion for lighting

0 20 40 60 80 100 US PAC CA Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US PAC CA Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US PAC CA Site Consumption kilowatthours $0 $250 $500 $750 $1,000 $1,250 $1,500 US PAC CA Expenditures dollars ELECTRICITY ONLY average per household ï‚· California households use 62 million Btu of energy per home, 31% less than the U.S. average. The lower than average site consumption results in households spending 30% less for energy than the U.S. average. ï‚· Average site electricity consumption in California homes is among the lowest in the nation, as the mild climate in much of the state leads to less reliance on

0 20 40 60 80 100 US PAC CA Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US PAC CA Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US PAC CA Site Consumption kilowatthours $0 $250 $500 $750 $1,000 $1,250 $1,500 US PAC CA Expenditures dollars ELECTRICITY ONLY average per household ï‚· California households use 62 million Btu of energy per home, 31% less than the U.S. average. The lower than average site consumption results in households spending 30% less for energy than the U.S. average. ï‚· Average site electricity consumption in California homes is among the lowest in the nation, as the mild climate in much of the state leads to less reliance on

Abstract In this study, Vitis vinifera L wines cv. Cabernet Franc, Merlot, Sangiovese and Syrah, 2006 and 2007 vintages, produced in São Joaquim, a new wine-producing region in southern Brazil, were evaluated. As phenolic compound content is one of the most important parameters in assessing wine quality and is possibly partially responsible for the beneficial health properties of wines, in this paper the levels of the main anthocyanins, flavonols, hydroxycinnamic acid and hydroxybenzoic acid (HPLC-DAD and HPLC-DAD–MS analysis) and the in vivo antioxidant activity in mice are reported. The antioxidant capacity of plasma was assessed through the reduction of ferric iron (FRAP). Lipid peroxidation (TBARS), carbonyl protein (CP), reduced glutathione (GSH) levels and the catalase (CAT), superoxide dismutase (SOD) and glutathione peroxidase (GPx) activity were determined in livers of the test animals. The results for the phenolic compounds content of the wine samples were considered appropriate for quality red wines, and the wine consumption promoted a significant increase in FRAP and decreases in the TBARS and CP levels and in the CAT, SOD and \\{GPx\\} activity. Moreover, the phenolic content of the wines was positively correlated with the in vivo antioxidant capacity promoted by regular wine consumption.

F (2001) -- Household Natural Gas Usage Form F (2001) -- Household Natural Gas Usage Form OMB No. 1905-0092, Expiring February 29, 2004 2001 Residential Energy Consumption Survey Answers to Frequently Asked Questions About the Household Natural Gas Usage Form What is the purpose of the Residential Energy Consumption Survey? The Residential Energy Consumption Survey (RECS) collects data on energy consumption and expenditures in U.S. housing units. Over 5,000 statistically selected households across the U.S. have already provided information about their household, the physical characteristics of their housing unit, their energy-using equipment, and their energy suppliers. Now we are requesting the energy billing records for these households from each of their energy suppliers. After all this information has been collected, the information will be used to

E (2001) - Household Electricity Usage Form E (2001) - Household Electricity Usage Form OMB No. 1905-0092, Expiring February 29, 2004 2001 Residential Energy Consumption Survey Answers to Frequently Asked Questions About the Household Electricity Usage Form What is the purpose of the Residential Energy Consumption Survey? The Residential Energy Consumption Survey (RECS) collects data on energy consumption and expenditures in U.S. housing units. Over 5,000 statistically selected households across the U.S. have already provided information about their household, the physical characteristics of their housing unit, their energy-using equipment, and their energy suppliers. Now we are requesting the energy billing records for these households from each of their energy suppliers. After all this information has been collected, the information will be used to

GA GA Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US SoAtl GA Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 4,000 8,000 12,000 16,000 US SoAtl GA Site Consumption kilowatthours $0 $300 $600 $900 $1,200 $1,500 $1,800 US SoAtl GA Expenditures dollars ELECTRICITY ONLY average per household * Site energy consumption (89.5 million Btu) and energy expenditures per household ($2,067) in Georgia are similar to the U.S. household averages. * Per household electricity consumption in Georgia is among the highest in the country, but similar to other states in the South. * Forty-five percent of homes in Georgia were built since 1990, a characteristic typically associated with lower per householdconsumption. Georgia homes,

GA GA Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US SoAtl GA Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 4,000 8,000 12,000 16,000 US SoAtl GA Site Consumption kilowatthours $0 $300 $600 $900 $1,200 $1,500 $1,800 US SoAtl GA Expenditures dollars ELECTRICITY ONLY average per household * Site energy consumption (89.5 million Btu) and energy expenditures per household ($2,067) in Georgia are similar to the U.S. household averages. * Per household electricity consumption in Georgia is among the highest in the country, but similar to other states in the South. * Forty-five percent of homes in Georgia were built since 1990, a characteristic typically associated with lower per householdconsumption. Georgia homes,

IL IL Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US ENC IL Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US ENC IL Site Consumption kilowatthours $0 $250 $500 $750 $1,000 $1,250 $1,500 US ENC IL Expenditures dollars ELECTRICITY ONLY average per household * Illinois households use 129 million Btu of energy per home, 44% more than the U.S. average. * High consumption, combined with low costs for heating fuels compared to states with a similar climate, result in Illinois households spending 2% more for energy than the U.S. average. * Less reliance on electricity for heating, as well as cool summers keeps average site electricity consumption in the state low relative to other parts of the U.S.

Sample records for household consumption profiles from the National Library of Energy Beta (NLEBeta)

Note: This page contains sample records for the topic "household consumption profiles" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.

IL IL Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US ENC IL Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US ENC IL Site Consumption kilowatthours $0 $250 $500 $750 $1,000 $1,250 $1,500 US ENC IL Expenditures dollars ELECTRICITY ONLY average per household * Illinois households use 129 million Btu of energy per home, 44% more than the U.S. average. * High consumption, combined with low costs for heating fuels compared to states with a similar climate, result in Illinois households spending 2% more for energy than the U.S. average. * Less reliance on electricity for heating, as well as cool summers keeps average site electricity consumption in the state low relative to other parts of the U.S.

MI MI Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US ENC MI Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US ENC MI Site Consumption kilowatthours $0 $250 $500 $750 $1,000 $1,250 $1,500 US ENC MI Expenditures dollars ELECTRICITY ONLY average per household * Michigan households use 123 million Btu of energy per home, 38% more than the U.S. average. * High consumption, combined with low costs for heating fuels compared to states with a similar climate, result in Michigan households spending 6% more for energy than the U.S. average. * Less reliance on electricity for heating, as well as cool summers keeps average site electricity consumption in the state low relative to other parts of the U.S.

MI MI Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US ENC MI Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US ENC MI Site Consumption kilowatthours $0 $250 $500 $750 $1,000 $1,250 $1,500 US ENC MI Expenditures dollars ELECTRICITY ONLY average per household * Michigan households use 123 million Btu of energy per home, 38% more than the U.S. average. * High consumption, combined with low costs for heating fuels compared to states with a similar climate, result in Michigan households spending 6% more for energy than the U.S. average. * Less reliance on electricity for heating, as well as cool summers keeps average site electricity consumption in the state low relative to other parts of the U.S.

120 120 US ENC WI Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US ENC WI Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US ENC WI Site Consumption kilowatthours $0 $300 $600 $900 $1,200 $1,500 US ENC WI Expenditures dollars ELECTRICITY ONLY average per household * Wisconsin households use 103 million Btu of energy per home, 15% more than the U.S. average. * Lower electricity and natural gas rates compared to states with a similar climate, such as New York, result in households spending 5% less for energy than the U.S. average. * Less reliance on electricity for heating, as well as cool summers, keeps average site electricity consumption in the state low relative to other parts of the U.S.

120 120 US ENC WI Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US ENC WI Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US ENC WI Site Consumption kilowatthours $0 $300 $600 $900 $1,200 $1,500 US ENC WI Expenditures dollars ELECTRICITY ONLY average per household * Wisconsin households use 103 million Btu of energy per home, 15% more than the U.S. average. * Lower electricity and natural gas rates compared to states with a similar climate, such as New York, result in households spending 5% less for energy than the U.S. average. * Less reliance on electricity for heating, as well as cool summers, keeps average site electricity consumption in the state low relative to other parts of the U.S.

WSC TX WSC TX Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US WSC TX Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 4,000 8,000 12,000 16,000 US WSC TX Site Consumption kilowatthours $0 $500 $1,000 $1,500 $2,000 US WSC TX Expenditures dollars ELECTRICITY ONLY average per household * Texas households consume an average of 77 million Btu per year, about 14% less than the U.S. average. * Average electricity consumption per Texas home is 26% higher than the national average, but similar to the amount used in neighboring states. * The average annual electricity cost per Texas household is $1,801, among the highest in the nation, although similar to other warm weather states like Florida. * Texas homes are typically newer, yet smaller in size, than homes in other parts of

WSC TX WSC TX Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US WSC TX Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 4,000 8,000 12,000 16,000 US WSC TX Site Consumption kilowatthours $0 $500 $1,000 $1,500 $2,000 US WSC TX Expenditures dollars ELECTRICITY ONLY average per household * Texas households consume an average of 77 million Btu per year, about 14% less than the U.S. average. * Average electricity consumption per Texas home is 26% higher than the national average, but similar to the amount used in neighboring states. * The average annual electricity cost per Texas household is $1,801, among the highest in the nation, although similar to other warm weather states like Florida. * Texas homes are typically newer, yet smaller in size, than homes in other parts of

ESC TN ESC TN Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US ESC TN Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 4,000 8,000 12,000 16,000 US ESC TN Site Consumption kilowatthours $0 $400 $800 $1,200 $1,600 US ESC TN Expenditures dollars ELECTRICITY ONLY average per household * Tennessee households consume an average of 79 million Btu per year, about 12% less than the U.S. average. * Average electricity consumption for Tennessee households is 33% higher than the national average and among the highest in the nation, but spending for electricity is closer to average due to relatively low electricity prices. * Tennessee homes are typically newer, yet smaller in size, than homes in other parts of the country.

......to seven households over a period...edition of the Energy Efficiency Action Plan...Consumption. Energy Efficiency in Household Appliances...Council on energy efficiency and repealing...Standards-Households in the informations......

Survey Results: Total Energy Consumption, Survey Results: Total Energy Consumption, Expenditures, and Intensities (2005) Dataset Summary Description The Residential Energy Consumption Survey (RECS) is a national survey that collects residential energy-related data. The 2005 survey collected data from 4,381 households in housing units statistically selected to represent the 111.1 million housing units in the U.S. Data were obtained from residential energy suppliers for each unit in the sample to produce the Consumption & Expenditures data. The Consumption & Expenditures and Intensities data is divided into two parts: Part 1 provides energy consumption and expenditures by census region, population density, climate zone, type of housing unit, year of construction and ownership status; Part 2 provides the same data according to household size, income category, race and age. The next update to the RECS survey (2009 data) will be available in 2011.

1 1 Transportation logo printer-friendly version logo for Portable Document Format file Household Vehicles Energy Consumption 1991 December 1993 Release Next Update: August 1997. Based on the 1991 Residential Transportation Energy Consumption Survey conducted by the Energy Information Administration (EIA) - survey series has been discontinued after EIA's 1994 survey. Only light-duty vehicles and recreational vehicles are included in this report. EIA has excluded motorcycles, mopeds, large trucks, and buses. This report, Household Vehicles Energy Consumption 1991, is based on data from the 1991 Residential Transportation Energy Consumption Survey (RTECS). Focusing on vehicle miles traveled (VMT) and energy enduse consumption and expenditures by households for personal transportation, the 1991 RTECS is

Public perceptions of energy consumption and savings Shahzeen Z. Attaria,1 , Michael L. De consumption and savings for a variety of household, transportation, and recycling activities. When asked, with 98% of US emissions attributed to energy consumption (2). According to Pacala and Socolow (3

WNC MO WNC MO Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US WNC MO Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 3,000 6,000 9,000 12,000 15,000 US WNC MO Site Consumption kilowatthours $0 $300 $600 $900 $1,200 $1,500 US WNC MO Expenditures dollars ELECTRICITY ONLY average per household * Missouri households consume an average of 100 million Btu per year, 12% more than the U.S. average. * Average household energy costs in Missouri are slightly less than the national average, primarily due to historically lower residential electricity prices in the state. * Missouri homes are typically larger than homes in other states and are more likely to be attached or detached single-family housing units.

Mnt(N) CO Mnt(N) CO Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US Mnt(N) CO Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US Mnt(N) CO Site Consumption kilowatthours $0 $250 $500 $750 $1,000 $1,250 $1,500 US Mnt(N) CO Expenditures dollars ELECTRICITY ONLY average per household * Colorado households consume an average of 103 million Btu per year, 15% more than the U.S. average. * Average household energy costs in Colorado are 23% less than the national average, primarily due to historically lower natural gas prices in the state. * Average electricity consumption per household is lower than most other states, as Colorado residents do not commonly use electricity for main space heating, air

Mnt(N) CO Mnt(N) CO Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US Mnt(N) CO Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US Mnt(N) CO Site Consumption kilowatthours $0 $250 $500 $750 $1,000 $1,250 $1,500 US Mnt(N) CO Expenditures dollars ELECTRICITY ONLY average per household * Colorado households consume an average of 103 million Btu per year, 15% more than the U.S. average. * Average household energy costs in Colorado are 23% less than the national average, primarily due to historically lower natural gas prices in the state. * Average electricity consumption per household is lower than most other states, as Colorado residents do not commonly use electricity for main space heating, air

Sample records for household consumption profiles from the National Library of Energy Beta (NLEBeta)

Note: This page contains sample records for the topic "household consumption profiles" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.

SoAtl VA SoAtl VA Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US SoAtl VA Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 4,000 8,000 12,000 16,000 US SoAtl VA Site Consumption kilowatthours $0 $300 $600 $900 $1,200 $1,500 $1,800 US SoAtl VA Expenditures dollars ELECTRICITY ONLY average per household * Virginia households consume an average of 86 million Btu per year, about 4% less than the U.S. average. * Average electricity consumption and costs are higher for Virginia households than the national average, but similar to those in neighboring states where electricity is the most common heating fuel. * Virginia homes are typically newer and larger than homes in other parts of the country. CONSUMPTION BY END USE

Mnt(S) AZ Mnt(S) AZ Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US Mnt(S) AZ Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 3,000 6,000 9,000 12,000 15,000 US Mnt(S) AZ Site Consumption kilowatthours $0 $500 $1,000 $1,500 $2,000 US Mnt(S) AZ Expenditures dollars ELECTRICITY ONLY average per household * Arizona households use 66 million Btu of energy per home, 26% less than the U.S. average. * The combination of lower than average site consumption of all energy, but above average electricity which is relatively expensive, results in Arizona households spending 3% less for energy than the U.S. average. * More reliance on air conditioning keeps average site electricity consumption in the state high relative to other parts of the U.S.

SoAtl VA SoAtl VA Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US SoAtl VA Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 4,000 8,000 12,000 16,000 US SoAtl VA Site Consumption kilowatthours $0 $300 $600 $900 $1,200 $1,500 $1,800 US SoAtl VA Expenditures dollars ELECTRICITY ONLY average per household * Virginia households consume an average of 86 million Btu per year, about 4% less than the U.S. average. * Average electricity consumption and costs are higher for Virginia households than the national average, but similar to those in neighboring states where electricity is the most common heating fuel. * Virginia homes are typically newer and larger than homes in other parts of the country. CONSUMPTION BY END USE

Mnt(S) AZ Mnt(S) AZ Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US Mnt(S) AZ Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 3,000 6,000 9,000 12,000 15,000 US Mnt(S) AZ Site Consumption kilowatthours $0 $500 $1,000 $1,500 $2,000 US Mnt(S) AZ Expenditures dollars ELECTRICITY ONLY average per household * Arizona households use 66 million Btu of energy per home, 26% less than the U.S. average. * The combination of lower than average site consumption of all energy, but above average electricity which is relatively expensive, results in Arizona households spending 3% less for energy than the U.S. average. * More reliance on air conditioning keeps average site electricity consumption in the state high relative to other parts of the U.S.

D (2001) -- Household Bottled Gas (LPG or Propane) Usage Form D (2001) -- Household Bottled Gas (LPG or Propane) Usage Form OMB No. 1905-0092, Expiring February 29, 2004 2001 Residential Energy Consumption Survey Answers to Frequently Asked Questions About the Household Bottled Gas (LPG or Propane) Usage Form What is the purpose of the Residential Energy Consumption Survey? The Residential Energy Consumption Survey (RECS) collects data on energy consumption and expenditures in U.S. housing units. Over 5,000 statistically selected households across the U.S. have already provided information about their household, the physical characteristics of their housing unit, their energy-using equipment, and their energy suppliers. Now we are requesting the energy billing records for these households from each of their energy suppliers. After all this information has been collected, the information will be used to

The discussion of theoretical, conceptual, and methodological concerns in the last three chapters has set the stage for an examination of the total effort that households devote to domestic and market activiti...

NE MA NE MA Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 $3,000 US NE MA Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US NE MA Site Consumption kilowatthours $0 $250 $500 $750 $1,000 $1,250 $1,500 US NE MA Expenditures dollars ELECTRICITY ONLY average per household * Massachusetts households use 109 million Btu of energy per home, 22% more than the U.S. average. * The higher than average site consumption results in households spending 22% more for energy than the U.S. average. * Less reliance on electricity for heating, as well as cool summers, keeps average site electricity consumption in the state low relative to other parts of the U.S. However, spending on electricity is closer to the national average due to higher

NE MA NE MA Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 $3,000 US NE MA Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US NE MA Site Consumption kilowatthours $0 $250 $500 $750 $1,000 $1,250 $1,500 US NE MA Expenditures dollars ELECTRICITY ONLY average per household * Massachusetts households use 109 million Btu of energy per home, 22% more than the U.S. average. * The higher than average site consumption results in households spending 22% more for energy than the U.S. average. * Less reliance on electricity for heating, as well as cool summers, keeps average site electricity consumption in the state low relative to other parts of the U.S. However, spending on electricity is closer to the national average due to higher

This paper draws on Chinese survey data to investigate variations in carbon dioxide emissions across households with different income levels. Rich households generate more emissions per capita than poor households via both their direct energy consumption and their higher expenditure on goods and services that use energy as an intermediate input. An econometric analysis confirms a positive relationship between emissions and income and establishes a slightly increasing marginal propensity to emit (MPE) over the relevant income range. The redistribution of income from rich to poor households is therefore shown to reduce aggregate household emissions, suggesting that the twin pursuits of reducing inequality and emissions can be achieved in tandem.

growth, China's energy consumption is rising at one of the fastest rates in the world, almost 8% per year over the period 2000-2010. Residential energy consumption has grown even faster than the national total . Although household energy consumption per capita is still low compared to the developed countries

Home Office Equipment Tables Home Office Equipment Tables (Million U.S. Households; 12 pages, 123 kb) Contents Pages HC7-1a. Home Office Equipment by Climate Zone, Million U.S. Households, 2001 1 HC7-2a. Home Office Equipment by Year of Construction, Million U.S. Households, 2001 1 HC7-3a. Home Office Equipment by Household Income, Million U.S. Households, 2001 1 HC7-4a. Home Office Equipment by Type of Housing Unit, Million U.S. Households, 2001 1 HC7-5a. Home Office Equipment by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 1 HC7-6a. Home Office Equipment by Type of Rented Housing Unit, Million U.S. Households, 2001 1 HC7-7a. Home Office Equipment by Four Most Populated States, Million U.S. Households, 2001 1

I provide a detailed description and in-depth analysis of household portfolios in Japan. (1) It is shown that the share of equities in financial wealth and the stock market participation of Japanese households decreased throughout the 1990s. (2) Using survey data, age-related variations in the share of stocks in financial wealth are analyzed. The equity share and stock market participation increase with age among young households, peaking when people reach their 50s, and then stabilizing. However, the share of equities conditional on ownership exhibits no significant age-related pattern, implying that age-related patterns are primarily explained by the decision to hold stocks. A similar mechanism operates to that found in previous studies of Western countries. (3) Owner-occupied housing has a significantly positive effect on stock market participation and on the share of stocks in financial wealth.

This paper presents the findings of an experimental study performed in 100 French households on the end-use power demand and energy consumption of domestic appliances focusing on cooking appliances [1].

Sample records for household consumption profiles from the National Library of Energy Beta (NLEBeta)

Note: This page contains sample records for the topic "household consumption profiles" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.

The U.S. Department of Energy (DOE) is conducting a national evaluation of its Weatherization Assistance Program, an energy efficiency program that provides financial assistance to qualifying low-income households for the {open_quotes}weatherization{close_quotes} of their housing units. The evaluation, being conducted for the Department by Oak Ridge National Laboratory (ORNL), is comprised of five studies. One of the five is a two-part analysis of the scope of the Weatherization Assistance Program and other resources devoted to low-income energy efficiency, including the number of dwellings weatherized to date and the population remaining to be served. This study is referred to here as the {open_quotes}Scope{close_quotes} study. This report presents the results of the second part of the {open_quotes}Scope{close_quotes} study, which investigates the characteristics of the population eligible for and in need of the DOE Weatherization Assistance Program - The Profile of the Population in Need. The {open_quotes}Profile{close_quotes} study is an attempt to use the Energy Information Administration`s Residential Energy Consumption Survey (RECS) for 1990 to define the weatherization-related characteristics of the low-income population. The RECS, a national survey with a sample size of 5,095 households, is the most reliable source for information regarding residential energy-use and housing characteristics because data is collected from fuel vendors on actual household energy bills and consumption for a large and representative sample of households.

...size and n* the average family size of the...equilibrium, the average of all the households...hand, nor is wood fuel easily accessible...recede. The relative prices of alternative...denoted by X: the average consumption level of...N is large, the effect of household h’s choice...

A group of 20 households was established to study whether we can motivate environmentally sustainable behaviour by providing homeowners with a clear picture of their impact, tangible reasons for improvement, and tailored solutions to follow. Reports for each household compared heating fuel, electricity, water, vehicle fuel/waste generation within the group and recommended cost-effective measures to reduce consumption. On average, 26% of the recommended measures were implemented, resulting in an estimated greenhouse gas reduction of about 2 tonnes per household. Wide variations were found between households, demonstrating the potential to reduce environmental impact through lifestyle, conservation, and energy conscious retrofits.

We investigated the relationship between electrical power consumption per capita and GDP per capita in 130 countries using the data reported by World Bank. We found that an electrical power consumption per capita...

Abstract New energy efficient lighting technologies can significantly reduce household electricity consumption, but adoption has been slow. A unique dataset of German households is used in this paper to examine the factors associated with the replacement of old incandescent lamps (ILs) with new energy efficient compact fluorescent lamps (CFLs) and light emitting diodes (LEDs). The ‘rebound’ effect of increased lamp luminosity in the transition to energy efficient bulbs is analyzed jointly with the replacement decision to account for household self-selection in bulb-type choice. Results indicate that the EU ban on \\{ILs\\} accelerated the pace of transition to \\{CFLs\\} and LEDs, while storage of bulbs significantly dampened the speed of the transition. Higher lighting needs and bulb attributes like energy efficiency, environmental friendliness, and durability spur IL replacement with \\{CFLs\\} or LEDs. Electricity gains from new energy efficient lighting are mitigated by 23% and 47% increases in luminosity for CFL and LED replacements, respectively. Model results suggest that taking the replacement bulb from storage and higher levels of education dampen the magnitude of these luminosity rebounds in IL to CFL transitions.

Air Conditioning Tables Air Conditioning Tables (Million U.S. Households; 24 pages, 138 kb) Contents Pages HC4-1a. Air Conditioning by Climate Zone, Million U.S. Households, 2001 2 HC4-2a. Air Conditioning by Year of Construction, Million U.S. Households, 2001 2 HC4-3a. Air Conditioning by Household Income, Million U.S. Households, 2001 2 HC4-4a. Air Conditioning by Type of Housing Unit, Million U.S. Households, 2001 2 HC4-5a. Air Conditioning by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 2 HC4-6a. Air Conditioning by Type of Rented Housing Unit, Million U.S. Households, 2001 2 HC4-7a. Air Conditioning by Four Most Populated States, Million U.S. Households, 2001 2 HC4-8a. Air Conditioning by Urban/Rural Location, Million U.S. Households, 2001 2

Energy Consumption Energy Consumption Transportation Energy Consumption Surveys energy used by vehicles EIA conducts numerous energy-related surveys and other information programs. In general, the surveys can be divided into two broad groups: supply surveys, directed to the suppliers and marketers of specific energy sources, that measure the quantities of specific fuels produced for and/or supplied to the market; and consumption surveys, which gather information on the types of energy used by consumer groups along with the consumer characteristics that are associated with energy use. In the transportation sector, EIA's core consumption survey was the Residential Transportation Energy Consumption Survey. RTECS belongs to the consumption group because it collects information directly from the consumer, the household. For roughly a decade, EIA fielded the RTECS--data were first collected in 1983. This survey, fielded for the last time in 1994, was a triennial survey of energy use and expenditures, vehicle miles-traveled (VMT), and vehicle characteristics for household vehicles. For the 1994 survey, a national sample of more than 3,000 households that own or use some 5,500 vehicles provided data.

MidAtl PA MidAtl PA Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 $3,000 US MidAtl PA Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US MidAtl PA Site Consumption kilowatthours $0 $250 $500 $750 $1,000 $1,250 $1,500 US MidAtl PA Expenditures dollars ELECTRICITY ONLY average per household * Pennsylvania households consume an average of 96 million Btu per year, 8% more than the U.S. average. Pennsylvania residents also spend 16% more than the average U.S. households for energy consumed in their homes. * Average electricity consumption in Pennsylvania homes is 10,402 kWh per year, which is lower than the national average, but 58% more than New York households and 17% more than New Jersey residents.

MidAtl PA MidAtl PA Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 $3,000 US MidAtl PA Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US MidAtl PA Site Consumption kilowatthours $0 $250 $500 $750 $1,000 $1,250 $1,500 US MidAtl PA Expenditures dollars ELECTRICITY ONLY average per household * Pennsylvania households consume an average of 96 million Btu per year, 8% more than the U.S. average. Pennsylvania residents also spend 16% more than the average U.S. households for energy consumed in their homes. * Average electricity consumption in Pennsylvania homes is 10,402 kWh per year, which is lower than the national average, but 58% more than New York households and 17% more than New Jersey residents.

The U.S. DOE Residential Lighting End-Use Consumption Study aims to improve the understanding of lighting energy usage in U.S. residential dwellings using a regional estimation framework. The framework allows for the estimation of lamp usage and energy consumption 1) nationally and by region of the United States, 2) by certain household characteristics, 3) by location within the home, 4) by certain lamp characteristics, and 5) by certain categorical cross-classifications.

Tobacco consumption is the use of tobacco products in different forms such as , , , water-pipes or tobacco products. Cigarettes and tobacco products containing tobacco are highly engineered so as to creat...

Transportation logo printer-friendly version logo for Portable Document Format file Household Vehicles Energy Use: Latest Data & Trends November 2005 Release (Next Update: Discontinued) Based on the 2001 National Household Travel Survey conducted by the U.S. Department of Transportation and augmented by EIA Only light-duty vehicles and recreational vehicles are included in this report. EIA has excluded motorcycles, mopeds, large trucks, and buses in an effort to maintain consistency with its past residential transportation series, which was discontinued after 1994. This report, Household Vehicles Energy Use: Latest Data & Trends, provides details on the nation's energy use for household passenger travel. A primary purpose of this report is to release the latest consumer-based data

Sample records for household consumption profiles from the National Library of Energy Beta (NLEBeta)

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MidAtl NY MidAtl NY Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 $3,000 US MidAtl NY Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US MidAtl NY Site Consumption kilowatthours $0 $250 $500 $750 $1,000 $1,250 $1,500 US MidAtl NY Expenditures dollars ELECTRICITY ONLY average per household * New York households consume an average of 103 million Btu per year, 15% more than the U.S. average. * Electricity consumption in New York homes is much lower than the U.S. average, because many households use other fuels for major energy end uses like space heating, water heating, and cooking. Electricity costs are closer to the national average due to higher than average electricity prices in the state.

MidAtl NY MidAtl NY Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 $3,000 US MidAtl NY Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US MidAtl NY Site Consumption kilowatthours $0 $250 $500 $750 $1,000 $1,250 $1,500 US MidAtl NY Expenditures dollars ELECTRICITY ONLY average per household * New York households consume an average of 103 million Btu per year, 15% more than the U.S. average. * Electricity consumption in New York homes is much lower than the U.S. average, because many households use other fuels for major energy end uses like space heating, water heating, and cooking. Electricity costs are closer to the national average due to higher than average electricity prices in the state.

193/P 193/P PRELIMINARY CONSERVATION TABLES FROM THE NATIONAL INTERIM ENERGY CONSUMPTION SURVEY OFFICE OF THE CONSUMPTION DATA SYSTEM OFFICE OF PROGRAM DEVELOPMENT ENERGY INFORMATION ADMINISTRATION AUGUST 1, 1979 PRELIMINARY CONSERVATION TABLES FROM THE NATIONAL INTERIM ENERGY CONSUMPTION SURVEY Attached is the first report of the Office of the Consumption Data System, Office of Program Development, Energy Information Administration, presenting preliminary data from the National Interim Energy Consumption Survey (NIECS). The focus of this report is the conservation activities performed by households since January 1977, and the status of households with respect to insulation, storm windows, and other energy conserving characteristics. These tables are from preliminary data files.

CONSUMPTION AND CHANGES IN HOME ENERGY COSTS: HOW PREVALENT IS THE `HEAT OR EAT' DECISION?Â· Julie how householdconsumption responds to changes in home energy outlays over the course of the year. We specify Euler equations describing nondurable and food consumption and then rely on changes in energy

This study assesses the influence of attitudinal and socio-economic factors on household energy conservation actions. A household interview survey in Regina, Saskatchewan found that respondents perceive an energy problem, although no association with energy conservation actions was determined. Two attitudinal and five socio-economic variables influence household energy conservation. Energy and monetary savings are available to households through energy conservation. Public awareness of household energy conservation through the media can reinforce existing energy conservation actions and encourage new actions.

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Who is eating seafood? On an annual basis, results from the survey screener showed that 65% of U.S. households purchased seafood for at-home consumption at least once in the previous year while 83% of households purchased seafood in a restaurant during the same period. As shown in Figures 1a-c, retail seafood

In this chapter we study the consumption behavior of an agent in the dynamic framework of consumption/investment decision making that allows the presence of a subsistence consumption level and the possibility of ...

Abstract: This chapter aims to evaluate the relationship between one of the recent healthcare reforms in the People’s Republic of China and household decisions both in terms of out-of-pocket expenditure and saving. Evidence on the results achieved by reforms of the health insurance sector in terms of reducing out-of-pocket medical expenditure is still uncertain and contradictory, and very little is known about the effect of these measures on the consumption and saving behaviour of the Chinese population. To shed light on this issue we use data collected by Chinese Household Income Project surveys (CHIPs), through a series of questionnaire-based interviews conducted in urban areas in 1995 and 2002. Our descriptive analysis suggests that there is a positive relationship between public health insurance coverage and household saving. This empirical evidence suggests that public insurance coverage is ineffective as a source of protection against income losses and might induce households to save more.

Abstract Various ecological footprint calculators, carbon footprint calculators and water footprint calculators have been developed in recent years. The basic concepts of ecological behaviour record notebooks and of carbon dioxide emission calculators have been developed since the late 20th century. The first carbon dioxide emission calculator was developed in 1991. Likewise, water pollutant discharge calculators have been developed to estimate the effects of soft measures introduced into households to reduce pollutant discharge since 2004. The soft measures which have been developed in Japan may consist of a wider framework, household sustainable consumption, which has been developed in Europe, and can be referred to cleaner consumption. In this research, summarisation of the short history of ecological behaviour record notebooks and ecological footprint calculators in Japan since the 1980s was conducted, and the soft measures in households to reduce pollutant discharge were evaluated for their effects on ambient water quality improvement as well as household and industry economies. Effects of the soft measures on related industry economies were investigated using an Input–Output Table analysis and the effects of the imported goods were evaluated with an import effect matrix, which was developed in this research. The effects of the soft measures on household expenditures were estimated to be a decrease by 2.5% or USD 285 person?1 year?1 in 2003–2006. The results show that the soft measures positively affect the chemical fibre industry and significantly affect the detergent industry. Analysis of the import effect matrix proved that the six industries were tightly related through extensive amounts of imported goods. The soft measures in households may lead to household sustainable consumption and thus reduce disadvantageous human impacts on water environments. The effects of the measures introduced to improve the environment should be qualitatively and quantitatively evaluated to avoid redundant concerns and discord between the environment and the economy, which may be worried when the relationship is not well understood.

Development of the Household Sample for Furnace and Boiler Life-Cycle Cost Development of the Household Sample for Furnace and Boiler Life-Cycle Cost Analysis Title Development of the Household Sample for Furnace and Boiler Life-Cycle Cost Analysis Publication Type Report LBNL Report Number LBNL-55088 Year of Publication 2005 Authors Whitehead, Camilla Dunham, Victor H. Franco, Alexander B. Lekov, and James D. Lutz Document Number LBNL-55088 Pagination 22 Date Published May 31 Publisher Lawrence Berkeley National Laboratory City Berkeley Abstract Residential household space heating energy use comprises close to half of all residential energy consumption. Currently, average space heating use by household is 43.9 Mbtu for a year. An average, however, does not reflect regional variation in heating practices, energy costs, or fuel type. Indeed, a national average does not capture regional or consumer group cost impacts from changing efficiency levels of heating equipment. The US Department of Energy sets energy standards for residential appliances in, what is called, a rulemaking process. The residential furnace and boiler efficiency rulemaking process investigates the costs and benefits of possible updates to the current minimum efficiency regulations. Lawrence Berkeley National Laboratory (LBNL) selected the sample used in the residential furnace and boiler efficiency rulemaking from publically available data representing United States residences. The sample represents 107 million households in the country. The data sample provides the household energy consumption and energy price inputs to the life-cycle cost analysis segment of the furnace and boiler rulemaking. This paper describes the choice of criteria to select the sample of houses used in the rulemaking process. The process of data extraction is detailed in the appendices and is easily duplicated.The life-cycle cost is calculated in two ways with a household marginal energy price and a national average energy price. The LCC results show that using an national average energy price produces higher LCC savings but does not reflect regional differences in energy price.

Energy and Resources Group, University of California, Berkeley, California 94720-3050, Risk, Resource, and Environmental Management Division, Resources for the Future, 1616 P Street NW, Washington, D.C. 20036, and Goldman School of Public Policy, University of California, Berkeley, California 94720-7320 ... Household energy policy is further complicated because charcoal markets in many sub-Saharan African countries operate within a complex political economy that can be hard to characterize and still more difficult to regulate. ... While charcoal consumption carries a larger burden of GHG emissions than firewood use, it also has more potential to attract investment in GHG mitigation activities. ...

Water Flows in the Spanish Economy: Agri-Food Sectors, Trade and Households Diets in an Input-Output Framework ... So although we use the information from a SAM, since we leave as exogenous accounts the householdconsumption and foreign trade; it is not a traditional SAM analysis, but more an extended input-output analysis. ... The countries concerned are France, Germany, Portugal, Italy, UK, Netherlands, U.S., Belgium, China, and Japan. ...

A sensitivity study was made of the potential market penetration of residential energy efficiency as energy service ratio (ESR) improvements occurred in minority households, by age of house. The study followed a Minority Energy Assessment Model analysis of the National Energy Strategy projections of household energy consumption and prices, with majority, black, and Hispanic subgroup divisions. Electricity and total energy consumption and expenditure patterns were evaluated when the households` ESR improvement followed a logistic negative growth (i.e., market penetration) path. Earlier occurrence of ESR improvements meant greater discounted savings over the 22-year period.

Sample records for household consumption profiles from the National Library of Energy Beta (NLEBeta)

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What's new in our home energy use? What's new in our home energy use? RECS 2009 - Release date: March 28, 2011 First results from EIA's 2009 Residential Energy Consumption Survey (RECS) The 2009 RECS collected home energy characteristics data from over 12,000 U.S. households. This report highlights findings from the survey, with details presented in the Household Energy Characteristics tables. How we use energy in our homes has changed substantially over the past three decades. Over this period U.S. homes on average have become larger, have fewer occupants, and are more energy-efficient. In 2005, energy use per household was 95 million British thermal units (Btu) of energy compared with 138 million Btu per household in 1978, a drop of 31 percent. Did You Know? Over 50 million U.S. homes have three or more televisions.

Detailed Tables Detailed Tables Energy End Uses Ranked by Energy Consumption, 1989 The following 28 tables present detailed data describing the consumption of and expenditures for energy used by households in the residential sector. The data are presented at the national level, Census region and division levels, for climate zones and for the most populous States, as well as for other selected characteristics of households. This section provides assistance in reading the tables by explaining some of the headings for the categories of data. It also explains the use of the row and column factors to compute the relative standard error of the estimates given in the tables. Organization of the Tables The tables cover consumption and expenditures for six topical areas: Major Energy Source

Residential household space heating energy use comprises close to half of all residential energy consumption. Currently, average space heating use by household is 43.9 Mbtu for a year. An average, however, does not reflect regional variation in heating practices, energy costs, or fuel type. Indeed, a national average does not capture regional or consumer group cost impacts from changing efficiency levels of heating equipment. The US Department of Energy sets energy standards for residential appliances in, what is called, a rulemaking process. The residential furnace and boiler efficiency rulemaking process investigates the costs and benefits of possible updates to the current minimum efficiency regulations. Lawrence Berkeley National Laboratory (LBNL) selected the sample used in the residential furnace and boiler efficiency rulemaking from publically available data representing United States residences. The sample represents 107 million households in the country. The data sample provides the household energy consumption and energy price inputs to the life-cycle cost analysis segment of the furnace and boiler rulemaking. This paper describes the choice of criteria to select the sample of houses used in the rulemaking process. The process of data extraction is detailed in the appendices and is easily duplicated. The life-cycle cost is calculated in two ways with a household marginal energy price and a national average energy price. The LCC results show that using an national average energy price produces higher LCC savings but does not reflect regional differences in energy price.

A Consumption-Based GHG Inventory for the U.S. State of Oregon ... Many U.S. states conduct greenhouse gas (GHG) inventories to inform their climate change planning efforts. ... Accordingly, a consumption-based perspective opens new opportunities for many states and their local government partners to reduce GHG emissions, such as initiatives to advance lower-carbon public sector or householdconsumption, that are well within their sphere of influence. ...

Sample records for household consumption profiles from the National Library of Energy Beta (NLEBeta)

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ConsumptionConsumption Electricity Consumption EIA Electricity Consumption Estimates (million kWh) National Petroleum Council Assumption: The definition of electricity con- sumption and sales used in the NPC 1999 study is the equivalent ofwhat EIA calls "sales by utilities" plus "retail wheeling by power marketers." This A nn u al Gro wth total could also be called "sales through the distribution grid," 2o 99 99 to Sales by Utilities -012% #N/A Two other categories of electricity consumption tracked by EIA cover on site Retail Wheeling Sales by generation for host use. The first, "nonutility onsite direct use," covers the Power Marketen 212.25% #N/A traditional generation/cogeneration facilities owned by industrial or large All Sales Through Distribution

12/11/2009 1 Population, Consumption & the Environment Alex de Sherbinin Center for International of carbon in 2001 Â· The ecological footprint, a composite measure of consumption measured in hectares kind of consumption is bad for the environment? 2. How are population dynamics and consumption linked

An important element in the discussion regarding sustainable development in our part of the world is directed towards the large growth in private consumption, and the clash of interests that arises between this growth and sustainable development requirements. A considerable part of private consumption can be related to our houses and the living situations of which they are part. It is of considerable interest to obtain more knowledge about the variations in patterns and volumes of consumption between different living situations, as well as to explore the important factors behind these variations. The acquisition of this type of empirical knowledge is an important aim in the present study. It is based on the superior thesis that it is possible through land use and housing planning to achieve substantial changes in living situations and thus contribute to a development in a direction of ''sustainable production and consumption''. The article first sums up the state-of-art regarding research on relations between physical planning, householdconsumption and environment. A theoretical framework and the methods applied in a Norwegian research project acquiring new empirical knowledge into these relations are also presented. The project was intended to be finished by the end of year 2000. Parts of the investigations are, however, completed and the material has been analysed. Two different types of urban structure, Oslo and a small rural town, are included in the investigations. The article presents some of the findings and relates them to former research.

Abstract This study empirically investigates whether macroeconomic effects of fiscal policy are affected by the existence of rule-of-thumb households in Japan. Motivated by existing theoretical formulations, we estimate a consumption function as extended to a Markov switching model and divide the sample period into two parts depending on the share of rule-of-thumb (ROT) households. Subsequently, we estimate a Vector Autoregression (VAR) model to investigate the effects of two types of fiscal policy shock: unanticipated and anticipated. The results are subjected to robustness checks and reveal that the share of ROT households rises after large negative shocks (i.e., oil shock, economic bubble burst, Lehman shock), and then (unanticipated) fiscal policy shock stimulates private consumption more effectively in the high ROT households’ period.

EIA household energy use data now includes detail on 16 States EIA household energy use data now includes detail on 16 States RECS 2009 - Release date: March 28, 2011 EIA is releasing new benchmark estimates for home energy use for the year 2009 that include detailed data for 16 States, 12 more than in past EIA residential energy surveys. EIA has conducted the Residential Energy Consumption Survey (RECS) since 1978 to provide data on home energy characteristics, end uses of energy, and expenses for the four Census Regions and nine Divisions. In 1997, EIA produced additional tabulations for the four most populous States (California, New York, Texas, and Florida). A threefold increase in the number of households included in the 2009 RECS offers more accuracy and coverage for understanding energy usage for all estimated States, Regions and Divisions.

Commercial household refrigerators use simple, cost-effective, temperature controllers to obtain acceptable control. A manually adjusted airflow damper regulates the freezer compartment temperature while a thermostat controls operation of the compressor and evaporator fan to regulate refrigerator compartment temperature. Dual compartment temperature control can be achieved with automatic airflow dampers that function independently of the compressor and evaporator fan thermostat, resulting in improved temperature control quality and energy consumption. Under dual control, freezer temperature is controlled by the thermostat while the damper controls refrigerator temperature by regulating airflow circulation. A simulation model is presented that analyzes a household refrigerator configured with a conventional thermostat and both manual and automatic dampers. The model provides a new paradigm for investigating refrigerator systems and temperature control performance relative to the extensive verification testing that is typically done by manufacturers. The effects of each type of control and damper configuration are compared with respect to energy usage, control quality, and ambient temperature shift criteria. The results indicate that the appropriate control configuration can have significant effects and can improve plant performance.

The energy efficiency of electric appliances has increased markedly in OECD countries, according to data provided by utilities, appliance associations, appliance manufacturers, and independent analyses of each country we reviewed (US, Sweden, Norway, Holland, Japan, Germany, UK). These improvements have, in part, offset increases in electricity demand due to increasing saturation of appliances. However, we see evidence that the efficiency of new devices has hit a temporary plateau: Appliances sold in 1988, while far more efficient than similar ones sold in the early 1970s, may not be significantly more efficient than those sold in 1987. The reason for this plateau, according to manufacturers we interviewed, is that the simple energy-saving features have been incorporated; more sophisticated efficiency improvements are economically justified by five to ten year paybacks, but unattractive to consumers in most countries who appear to demand paybacks of less than three years. Manufacturers see features other than efficiency --- such as number of storage compartments and automatic ice-makers --- as more likely to boost sales, market share, or profits. If this efficiency plateau'' proves lasting, then electricity use for appliance could begin to grow again as larger and more fancy models appear in households. 38 refs., 10 figs., 1 tab.

Sample records for household consumption profiles from the National Library of Energy Beta (NLEBeta)

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This report provides estimates on energy consumption in the manufacturing sector of the U.S. economy based on data from the Manufacturing Energy Consumption Survey. The sample used in this report represented about 250,000 of the largest manufacturing establishments which account for approximately 98 percent of U.S. economic output from manufacturing, and an expected similar proportion of manufacturing energy use. The amount of energy use was collected for all operations of each establishment surveyed. Highlights of the report include profiles for the four major energy-consuming industries (petroleum refining, chemical, paper, and primary metal industries), and an analysis of the effects of changes in the natural gas and electricity markets on the manufacturing sector. Seven appendices are included to provide detailed background information. 10 figs., 51 tabs.

Share of energy used by appliances and consumer electronics increases in Share of energy used by appliances and consumer electronics increases in U.S. homes RECS 2009 - Release date: March 28, 2011 Over the past three decades, the share of residential electricity used by appliances and electronics in U.S. homes has nearly doubled from 17 percent to 31 percent, growing from 1.77 quadrillion Btu (quads) to 3.25 quads. This rise has occurred while Federal energy efficiency standards were enacted on every major appliance, overall household energy consumption actually decreased from 10.58 quads to 10.55 quads, and energy use per household fell 31 percent. Federal energy efficiency standards have greatly reduced consumption for home heating Total energy use in all U.S. homes occupied as primary residences decreased slightly from 10.58 quads in 1978 to 10.55 quads in 2005 as reported by the

Abstract In the literature, econometricians typically assume that household income is the sum of a random walk permanent component and a transitory component, with uncorrelated permanent and transitory shocks. Using data on realized individual incomes and individual expectations of future incomes from the Survey of Italian Households? Income and Wealth, I find that permanent and transitory shocks are negatively correlated. Relaxing the assumption of no correlation between the shocks, I explore the effects of correlated income shocks on the estimated consumption insurance against permanent and transitory shocks, and consumption smoothness using a life-cycle model with self-insurance calibrated to U.S. data. Negatively correlated income shocks result in smoother consumption, and upward-biased estimates of the insurance against transitory (and permanent when borrowing constraints are not tight) income shocks. While the life-cycle model with negatively correlated shocks fits well the sensitivity of consumption to current income shocks observed in U.S. data, it falls short of explaining the sensitivity of consumption to income shocks cumulated over a longer horizon.

The literature concerning the application of information-feedback methods for saving energy in the home is reviewed. Particular attention is given to electronic feedback via smart meters and displays, or “energy-consumption indicators” (ECI). Previous studies have not focused on individual appliances, but this paper presents the findings of a UK field study involving 44 households which considered domestic cooking: it compares the effectiveness of providing paper-based energy-use/saving information with electronic feedback of energy-consumption via \\{ECIs\\} designed specifically for this investigation. Twelve Control Group households were monitored for a period of at least 12 months and this revealed an average daily consumption for electric cooking of 1.30 kWh. Subsequently across a minimum monitoring period of 2 months, 14 out of 31 households achieved energy savings of greater than 10% and six of these achieved savings of greater than 20%. The average reduction for households employing an ECI was 15%, whereas those given antecedent information alone reduced their electricity consumption, on average, by only 3%. The associated behavioural changes and the importance of providing regular feedback during use are identified. It is recommended that further attention be given to optimising the design and assessing the use of energy-consumption indicators in the home, in order to maximise the associated energy-saving potential.

This study investigated the effect of door openings and kitchen environment on the energy consumption of nine household refrigerator/freezers (R/Fs) in the field. The factors under consideration include fresh food and freezer door openings, length of door openings, ambient kitchen temperature, and kitchen relative humidity (RH). Average daily energy consumption for the nine units ranged from 1.7 to 5.3 kWh/day. Energy consumption was found to correlate with kitchen temperature and the number of door openings. No dependence on kitchen relative humidity was found. In general, the magnitude of the door opening component of energy consumption was higher for the more efficient units.

ConsumptionConsumption The State Energy Data System (SEDS) comma-separated value (CSV) files contain consumption estimates shown in the tables located on the SEDS website. There are four files that contain estimates for all states and years. Consumption in Physical Units contains the consumption estimates in physical units for all states; Consumption in Btu contains the consumption estimates in billion British thermal units (Btu) for all states. There are two data files for thermal conversion factors: the CSV file contains all of the conversion factors used to convert data between physical units and Btu for all states and the United States, and the Excel file shows the state-level conversion factors for coal and natural gas in six Excel spreadsheets. Zip files are also available for the large data files. In addition, there is a CSV file for each state, named

The high ambient temperature of the Canadian Standards Association (CSA) and the AHAM/DOE Refrigerator-Freezer Energy Consumption Standards is intended to compensate for the lack of door openings and other heat loads. Recently published results by Meier and Jansky (1993) indicate labeled consumption overpredicting typical field consumption by 15%. In-house field studies on conventional models showed labeled consumption overpredicting by about 22%. The Refrigerator-Freezer Technology Assessment (RFTA) test was developed to more accurately predict field consumption. This test has ambient temperature and humidity, door openings, and condensation control set at levels intended to typify Canadian household conditions. It also assesses consumption at exactly defined compartment rating temperatures. Ten conventional and energy-efficient production models were laboratory tested. The RFTA results were about 30% lower than labeled. Similarly, the four innovative refrigerator-freezer models, when field tested, also had an average of 30% lower consumption than labeled. Thus, the results of the limited testing suggest that the RFTA test may be a more accurate predictor of field use. Further testing with a larger sample is recommended. Experimental results also indicated that some innovative models could save up to 50% of the energy consumption compared with similar conventional units. The technologies that contributed to this performance included dual compressors, more efficient compressors and fan motors, off-state refrigerant control valve, fuzzy logic control, and thicker insulation. The larger savings were on limited production models, for which additional production engineering is required for full marketability.

Home Page Welcome to the Energy Information Administration's Residential Transportation Energy Consumption Home Page. If you need assistance in viewing this page, please call (202) 586-8800 Home Page Welcome to the Energy Information Administration's Residential Transportation Energy Consumption Home Page. If you need assistance in viewing this page, please call (202) 586-8800 Home > Transportation Home Page > Special Topics Special Topics Change in Method for Estimating Fuel Economy for the 1988 and subsequent RTECS (Released 09/12/2000) Can Household Members Accurately Report How Many Miles Their Vehicles Are Driven? (Released 08/03/2000) Calculate your Regional Gasoline Costs of Driving using the Â“Transportation CalculatorÂ” updated for new model years! Choose your car or SUV and see the gasoline part of the cost of driving in various parts of the country using EIA's current weekly prices. This application uses DOE/EPA's Fuel Economy Guide to set the MPG, but you can change it to compare your estimate of your car's mpg to the average of everyone else who takes the test. (Released 04/11/2000; Updated Yearly for Fuel Economies and Weekly for Fuel Prices)

This study highlights the salient differences among various testing standards for household refrigerator-freezers and proposes a methodology for predicting the performance of a single evaporator-based vapor-compression refrigeration system (either refrigerator or freezer) from one test standard (where the test data are available-the reference case) to another (the alternative case). The standards studied during this investigation include the Australian-New Zealand Standard (ANZS), the International Standard (ISO), the American National Standard (ANSI), the Japanese Industrial Standard (JIS), and the Chinese National Standard (CNS). A simple analysis in conjunction with the BICYCLE model (Bansal and Rice 1993) is used to calculate the energy consumption of two refrigerator cabinets from the reference case to the alternative cases. The proposed analysis includes the effect of door openings (as required by the JIS) as well as defrost heaters. The analytical results are found to agree reasonably well with the experimental observations for translating energy consumption information from one standard to another.

Sample records for household consumption profiles from the National Library of Energy Beta (NLEBeta)

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they are not comprehensive nor are they the most current set.
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In this paper, we appraise sustainable householdconsumption from a global perspective. Using per capita energy requirements as an indicator of environmental pressure, we focus on the importance of income growth in a cross-country analysis. Our analysis is supported by a detailed within-country analysis encompassing five countries, in which we assess the importance of various socioeconomic-demographic characteristics of household energy requirements. We bring together family expenditure survey data, input–output tables, and energy statistics in a multivariate analysis. Instead of a uniform Kuznet's curve, we find that the effect of increasing income varies considerably across countries, even when controlling for socioeconomic and demographic variations. The latter variables show similar influences, but differing importance across countries.

Abstract Household energy conservation has emerged as a major challenge and opportunity for researchers, practitioners and policymakers. Consumers also seem to be gaining greater awareness of the value and need for sustainable energy practices, particularly amid growing public concerns over greenhouse gas emissions and climate change. Yet even with adequate knowledge of how to save energy and a professed desire to do so, many consumers still fail to take noticeable steps towards energy efficiency and conservation. There is often a sizeable discrepancy between peoples’ self-reported knowledge, values, attitudes and intentions, and their observable behaviour—examples include the well-known ‘knowledge-action gap’ and ‘value-action gap’. But neither is household energy consumption driven primarily by financial incentives and the rational pursuit of material interests. In fact, people sometimes respond in unexpected and undesirable ways to rewards and sanctions intended to shift consumers’ cost–benefit calculus in favour of sustainable behaviours. Why is this so? Why is household energy consumption and conservation difficult to predict from either core values or material interests? By drawing on critical insights from behavioural economics and psychology, we illuminate the key cognitive biases and motivational factors that may explain why energy-related behaviour so often fails to align with either the personal values or material interests of consumers. Understanding these psychological phenomena can make household and community responses to public policy interventions less surprising, and in parallel, can help us design more cost-effective and mass-scalable behavioural solutions to encourage renewable and sustainable energy use among consumers.

This paper provides a comparative analysis of household wealth in the United States, the United Kingdom, Japan, France, Germany, Spain, and Italy. ... wealth, looking at the instruments in which households invest...

Efficiency Efficiency Energy Efficiency energy consumption savings households, buildings, industry & vehicles The Energy Efficiency Page reflects EIA's information on energy efficiency and related information. This site provides an in depth discussion of the concept of energy efficiency and how it is measured, measurement, summaries of formal user meetings on energy efficiency data and measurement, as well as analysis of greenhouse gas emissions as related to energy use and energy efficiency. At the site you will find links to other sources of information, and via a listserv all interested analysts can share ideas, data, and ask for assistance on methodological problems associated with energy use, energy efficiency, and greenhouse gas issues. Contact: Behjat.Hojjati@eia.doe.gov

How does EIA estimate energy consumption and end uses in U.S. homes? How does EIA estimate energy consumption and end uses in U.S. homes? RECS 2009 - Release date: March 28, 2011 EIA administers the Residential Energy Consumption Survey (RECS) to a nationally representative sample of housing units. Specially trained interviewers collect energy characteristics on the housing unit, usage patterns, and household demographics. This information is combined with data from energy suppliers to these homes to estimate energy costs and usage for heating, cooling, appliances and other end uses Ã¢â‚¬" information critical to meeting future energy demand and improving efficiency and building design. RECS uses a multi-stage area probability design to select sample methodology figure A multi-stage area probability design ensures the selection

91/0 en Operational water 91/0 en Operational water consumption and withdrawal factors for electricity generating technologies http://en.openei.org/datasets/node/969 This dataset is from the report Operational water consumption and withdrawal factors for electricity generating technologies: a review of existing literature (J. Macknick, R. Newmark, G. Heath and K.C. Hallett) and provides estimates of operational water withdrawal and water consumption factors for electricity generating technologies in the United States. Estimates of water factors were collected from published primary literature and were not modified except for unit conversions.

Graduate School of Energy Science, Kyoto University, Gokasho, Uji, Kyoto 611-0011, Japan ... Next, for each of the 400 sectors (the 399 sectors of the consolidated Input?Output Table plus the “consumption expenditure of households” sector, which is one of the final demand sectors), various statistics and source materials were used to estimate gross consumptions, expressed as a physical amount for each sector, of 6 coal-based fuels, 12 petroleum-based fuels, 3 natural gas-based fuels, and 5 other fuels. ... LPG. LPG for automobile and household use is more expensive than that used by industry, because of its higher tax rate and less efficient mode of supply. ...

Sample records for household consumption profiles from the National Library of Energy Beta (NLEBeta)

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Acute caffeine consumption enhances the executive control of visual attention in habitual consumers vigilance and the executive control of visual attention in individuals with low caffeine consumptionconsumptionprofiles would show similar advantages. To this end, we examined the effects of four caffeine

Cooling systems using water evaporation to dissipate waste heat, will require one pound of water per 1,000 Btu. To reduce water consumption, a combination of "DRY" and "WET" cooling elements is the only practical answer. This paper reviews...

Calculating fuel consumption and emissions is a typical offline analysis ... simulations or real trajectory data) and the engine speed (as obtained from gear-shift schemes ... as input and is parameterized by veh...

...original work is properly cited. Food consumption trends and drivers John Kearney...Government policy. A picture of food consumption (availability) trends and projections...largely responsible for these observed consumption trends are the subject of this review...

About the RECS About the RECS RECS Survey Forms RECS Maps RECS Terminology Archived Reports State fact sheets Arizona household graph See state fact sheets â€º 2009 RECS Features Heating and cooling no longer majority of U.S. home energy use March 7, 2013 Newer U.S. homes are 30% larger but consume about as much energy as older homes February 12, 2013 Where does RECS square footage data come from? July 11, 2012 RECS data show decreased energy consumption per household June 6, 2012 The impact of increasing home size on energy demand April 19, 2012 Did you know that air conditioning is in nearly 100 million U.S. homes? August 19, 2011 See more > graph of U.S. electricity end use, as explained in the article text U.S. electricity sales have decreased in four of the past five years

About the RECS About the RECS RECS Survey Forms RECS Maps RECS Terminology Archived Reports State fact sheets Arizona household graph See state fact sheets â€º 2009 RECS Features Heating and cooling no longer majority of U.S. home energy use March 7, 2013 Newer U.S. homes are 30% larger but consume about as much energy as older homes February 12, 2013 Where does RECS square footage data come from? July 11, 2012 RECS data show decreased energy consumption per household June 6, 2012 The impact of increasing home size on energy demand April 19, 2012 Did you know that air conditioning is in nearly 100 million U.S. homes? August 19, 2011 See more > graph of U.S. electricity end use, as explained in the article text U.S. electricity sales have decreased in four of the past five years

About the RECS About the RECS RECS Survey Forms RECS Maps RECS Terminology Archived Reports State fact sheets Arizona household graph See state fact sheets â€º 2009 RECS Features Heating and cooling no longer majority of U.S. home energy use March 7, 2013 Newer U.S. homes are 30% larger but consume about as much energy as older homes February 12, 2013 Where does RECS square footage data come from? July 11, 2012 RECS data show decreased energy consumption per household June 6, 2012 The impact of increasing home size on energy demand April 19, 2012 Did you know that air conditioning is in nearly 100 million U.S. homes? August 19, 2011 See more > graph of U.S. electricity end use, as explained in the article text U.S. electricity sales have decreased in four of the past five years

RICE CONSUMPTION IN CHINA A Thesis by JIN LAN Submitted to the Office of Graduate Studies of Texas ASM University in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE August 1989 Major Subject: Agricultural... Economics RICE CONSUMPTION IN CHINA A Thesis by JIN LAN Approved as to style and content by: E, We ey F. Peterson (Chair of Committee) James E. Christiansen (Member) Carl Shaf (Member) Daniel I. Padberg (Head of Department) August 1989...

Research Center for Material Cycles and Waste Management, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan, Faculty of Economics, Kyushu University, 6-19-1 Hakozaki, Higashi-ku, Fukuoka, 812-8581, Japan, and Department of Bioproducts and Biosystems Engineering, College of Food, Agriculture and Natural Resources Sciences, University of Minnesota, 2004 Folwell Avenue, St. Paul, MN 55108, and Institute of Environmental Sciences (CML), Leiden University, P.O. ... Eq 8 thus determined Dt where Yt denotes the quantity of goods and services provided to households as measured in monetary units and Pt is the aggregate CO2 emissions due to Yt. ... The linked IOT defines electricity, petroleum fuels (gasoline, diesel, kerosene, liquid petroleum gas, etc.), and city gas as three separate sectors (commodities) but with no further breakdown of quantitative consumption or the uses to which the respective energy carriers are put, either nationally or at the household level. ...

ABSTRACT This paper describes the analytical and simulation capabilities of the currently implemented version of the “household model” developed by the Structural Analysis Division, Statistics Canada. The household model, as described in A Design Framework for Long Term Energy – Economic Analysis of Dwelling Related Demand [1], is a simulation framework and related data base of the Canadian housing stocks, residential construction, and end-use energy consumption in the residential sector. The purpose of the model is to provide an analytical tool for evaluating a variety of residential energy conservation strategies including insulation retrofitting and the introduction of new building standards, the possibilities for fuel substitution afforded by equipment retrofitting, and the impact of new technologies for space conditioning with respect to impacts on residential energy requirements and construction materials over time. The simulation results for Ontario that are presented in the paper are for demonstration purposes only and do not constitute a forecast. The choice of Ontario was arbitrary; similar calculations can be performed for other provinces, for Canada as a whole, and for selected subprovincial regions. At the time of preparation of this paper, the population and household formation block at the national level, the housing stock block, and the space heating part of the space conditioning block are implemented. Therefore simulation results are limited to these areas.

Abstract This paper examines the voluntary electricity-saving awareness of households after the Great East Japan Earthquake and the subsequent accident at the Fukushima nuclear power station. We conduct a conjoint analysis of consumer stated preferences for the settings of air conditioners, refrigerators, and the standby power of electrical appliances, based on a web questionnaire survey administered in the areas supplied by the Tokyo Electric Power Company (TEPCO) and Kansai Electric Power Company (KEPCO). The main findings of this paper are as follows. First, we observe awareness of voluntary electricity conservation among the households in both the TEPCO and KEPCO areas after the disasters. Second, awareness of voluntary power saving is higher in the TEPCO area, which has been directly affected by the electric power shortages, in comparison with the KEPCO area, where there was no such direct impact. Third, if power prices are to be further raised, the consumer responses to the price changes would be small in both areas. Furthermore, we show that the potential voluntary reduction in electric power consumption of a household in the TEPCO area is 26% more than that in the KEPCO area during the summer peak periods.

Papers in the literature have thus far overlooked the projected increase in U.S. diesel car share when looking at asymmetries in petroleum pricing. This paper addresses this issue by comparing retail gasoline and diesel prices in order to see whether they rise faster than they fall given the price of their upstream input, crude oil. This phenomenon has been termed in the literature as “Rockets and Feathers.” We apply the threshold vector error correction model (TVECM) of Hansen and Seo (2002) which has not yet been applied in the literature. We account for the 2008 structural break to crude oil and petroleum prices by splitting the sample using evidence from the recent structural break unit root test of Kim and Perron (2009). Both markets seem to price symmetrically before the 2008 break, but we find evidence of asymmetric pricing after 2008 in diesel prices, and not in gasoline prices. Given that the diesel market is small relative to the gasoline market and therefore more open to price exploitation, the ongoing cost increases associated with the policy of switching to Ultra Low Sulphur diesel (ULSD) from 2006 to 2010 could be at the heart of this asymmetry. With this in mind, the U.S. Federal Trade Commission should monitor diesel prices as the market share grows, in order to ensure that consumers are not adversely affected.

Indonesia is one of the most diverse countries in the world in terms of its society. Therefore, there are several different characteristics in daily practices, including in consuming electricity. In order to unde...

? scale?. This covers any energy generation that is decentralized. Micro-generation technologies may take the form of solar photovoltaic (PV), micro-wind turbines, micro-hydro or even micro-combined heat and power (CHP). Micro-generation provides energy...

Sample records for household consumption profiles from the National Library of Energy Beta (NLEBeta)

Note: This page contains sample records for the topic "household consumption profiles" from the National Library of EnergyBeta (NLEBeta).
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they are not comprehensive nor are they the most current set.
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Analysis and evaluation of the impact that programs and policies have on energy consumption and expenditures are confounded by many intervening variables. A clear understanding of how these variables influence energy consumption patterns should be grounded in a rigorously developed framework. In this regard much is documented in the literature. However, an analysis of the comparative relationship between energy demand and variables which influence it among different socioeconomic groups has not been thoroughly explored with any theoretical rigor. It is proposed that differences in patterns of energy use between black, Hispanic, and majority households (where the household head is neither black nor Hispanic) are due to both structural and distribution differences. It is felt that the structural dissimilarities are primarily due to the dynamic nature in which energy consumption patterns evolve, with differences in changing housing patterns playing a significant role. For minorities, this implies a potential difference in the effect of policy and programs on economic welfare when compared to majority households.To test this hypothesis, separate conditional demand systems are estimated for majority, black, and Hispanic households. With the use of separate variance/covariance matrices, various parameter groups are tested for statistically significant differences.

Analysis and evaluation of the impact that programs and policies have on energy consumption and expenditures are confounded by many intervening variables. A clear understanding of how these variables influence energy consumption patterns should be grounded in a rigorously developed framework. In this regard much is documented in the literature. However, an analysis of the comparative relationship between energy demand and variables which influence it among different socioeconomic groups has not been thoroughly explored with any theoretical rigor. It is proposed that differences in patterns of energy use between black, Hispanic, and majority households (where the household head is neither black nor Hispanic) are due to both structural and distribution differences. It is felt that the structural dissimilarities are primarily due to the dynamic nature in which energy consumption patterns evolve, with differences in changing housing patterns playing a significant role. For minorities, this implies a potential difference in the effect of policy and programs on economic welfare when compared to majority households.To test this hypothesis, separate conditional demand systems are estimated for majority, black, and Hispanic households. With the use of separate variance/covariance matrices, various parameter groups are tested for statistically significant differences.

† Industrial Ecology Programme and Department of Energy and Process Engineering, Norwegian University of Science and Technology (NTNU), Trondheim, Norway ... On the global level, the accounting for emissions embodied in trade increases the already high carbon footprints of Europe, Japan, South Korea, and the United States. ... On a global level, 72% of greenhouse gas emissions are related to householdconsumption, 10% to government consumption, and 18% to investments. ...

D (2005) - Household Propane (Bottled Gas or LPG) Usage Form D (2005) - Household Propane (Bottled Gas or LPG) Usage Form OMB No. 1905-0092, Expiring May 31, 2008 Household Propane (Bottled Gas or LPG) Usage Form Service Address: If the customer account number is not shown on the label, please enter it here. STEP 1 Customer Account: __/__/__/__/__/__/__/__/__/__/__/__/__/__/__/ STEP 2 Now, please turn the page and answer the seven questions for the household identified above. Completed forms are due by March 4, 2006. If you have any questions, please call (toll-free) 1-NNN-NNN-NNNN. Ask for the Supplier Survey Specialist. This report is mandatory under Public Law 93-275, as amended. See the enclosed Answers to Frequently Asked Questions for more details concerning confidentiality

F (2005) - Household Natural Gas Usage Form F (2005) - Household Natural Gas Usage Form OMB No. 1905-0092, Expiring May 31, 2008 Household Natural Gas Usage Form Service Address: If the customer account number is not shown above, please enter it here. STEP 1 Customer Account: __/__/__/__/__/__/__/__/__/__/__/__/__/__/__/ STEP 2 Now, please turn the page and provide the requested information for the household identified above. Completed forms are due by March 4, 2006. If you have any questions, please call (toll-free) 1-NNN-NNN-NNNN. Ask for the Supplier Survey Specialist. This report is mandatory under Public Law 93-275, as amended. See the enclosed Answers to Frequently Asked Questions for more details concerning confidentiality and sanctions. Use the enclosed self-addressed envelope and return the completed form to:

G (2005) - Household Fuel Oil or Kerosene Usage Form G (2005) - Household Fuel Oil or Kerosene Usage Form OMB No. 1905-0092, Expiring May 31, 2008 Household Fuel Oil or Kerosene Usage Form Service Address: If the customer account number is not shown on the label, please enter it here. STEP 1 Customer Account: __/__/__/__/__/__/__/__/__/__/__/__/__/__/__/ STEP 2 Now, please turn the page and answer the seven questions for the household identified above. Completed forms are due by March 4, 2006. If you have any questions, please call (toll-free) 1-NNN-NNN-NNNN. Ask for the Supplier Survey Specialist. This report is mandatory under Public Law 93-275, as amended. See the enclosed Answers to Frequently Asked Questions for more details concerning confidentiality and sanctions.

A general assessment of the range of barriers which impede household investments in weatherization and other energy efficiency improvements for their homes is provided. The relationship of similar factors to households' interest in receiving a free energy audits examined. Rates of return that underly household investments in major conservation improvements are assessed. A special analysis of household knowledge of economically attractive investments is provided that compares high payback improvements specified by the energy audit with the list of needed or desirable conservation improvements identified by respondents. (LEW)

Economic development disadvantages wives. Conventional microeconomic theory predicts this. As household incomes rise, wives have incentives to specialize in intangible household production. This may raise total household production according to the theory of comparative advantage, but disproportionately favors husbands in distribution of the gains according to the marginal productivity theory of distribution. Wives may become better off in absolute terms but more dependent financially on their husbands and lose power within the household. Historically, Japanese gender roles became highly specialized and wives’ legal status declined, although other Meiji-era features protected wives. Policies to improve women's status should address the precise economic problem involved.

......Figure 10. Providing Energy Feedback on multiple...checked their current energy consumption before...commercial breaks. The integration of the HEMS into...important factor for sustainable use. To an extent...provides significant challenge to householders...monitoring of their energy usage in situations......

About the RECS About the RECS RECS Survey Forms RECS Maps RECS Terminology Archived Reports State fact sheets Arizona household graph See state fact sheets â€º graph of U.S. electricity end use, as explained in the article text U.S. electricity sales have decreased in four of the past five years December 20, 2013 Gas furnace efficiency has large implications for residential natural gas use December 5, 2013 EIA publishes state fact sheets on residential energy consumption and characteristics August 19, 2013 All 48 related articles â€º Other End Use Surveys Commercial Buildings - CBECS Manufacturing - MECS Transportation About the RECS EIA administers the Residential Energy Consumption Survey (RECS) to a nationally representative sample of housing units. Specially trained interviewers collect energy characteristics on the housing unit, usage

The impact of increasing home size on energy demand The impact of increasing home size on energy demand RECS 2009 - Release date: April 19, 2012 Homes built since 1990 are on average 27% larger than homes built in earlier decades, a significant trend because most energy end-uses are correlated with the size of the home. As square footage increases, the burden on heating and cooling equipment rises, lighting requirements increase, and the likelihood that the household uses more than one refrigerator increases. Square footage typically stays fixed over the life of a home and it is a characteristic that is expensive, even impractical to alter to reduce energy consumption. According to results from EIA's 2009 Residential Energy Consumption Survey (RECS), the stock of homes built in the 1970s and 1980s averages less than

Center Power Consumption Center Power Consumption A new look at a growing problem Fact - Data center power density up 10x in the last 10 years 2.1 kW/rack (1992); 14 kW/rack (2007) Racks are not fully populated due to power/cooling constraints Fact - Increasing processor power Moore's law Fact - Energy cost going up 3 yr. energy cost equivalent to acquisition cost Fact - Iterative power life cycle Takes as much energy to cool computers as it takes to power them. Fact - Over-provisioning Most data centers are over-provisioned with cooling and still have hot spots November 2007 SubZero Engineering An Industry at the Crossroads Conflict between scaling IT demands and energy efficiency Server Efficiency is improving year after year Performance/Watt doubles every 2 years Power Density is Going Up

Sample records for household consumption profiles from the National Library of Energy Beta (NLEBeta)

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to generate environmental benefits through reducing water use, has produced economic incentives for households; France; households; domestic boreholes; tube well; water pricing. Author-produced version Fourth World negative environmental impact of water price increase in the drinking water sector. Using primary data

This study models the production and comsumption of residential space heat, a nonmarket good. Production reflects capital investment decisions of households; consumption reflects final demand decisions given the existing capital stock. In the model, the production relationship is represented by a translog cost equation and an anergy factor share equation. Consumption is represented by a log-linear demand equation. This system of three equations - cost, fuel share, and final demand - is estimated simultaneously. Results are presented for two cross-sections of households surveyed in 1973 and 1981. Estimates of own-price and cross-price elasticities of factor demand are of the correct sign, and less than one in magnitude. The price elasticity of final demand is about -0.4; the income elasticity of final demand is less than 0.1. Short-run and long-run elasticities of demand for energy are about -0.3 and -0.6, respectively. These results suggest that price-induced decreases in the use of energy for space heat are attributable equally to changes in final demand and to energy conservation, the substitution of capital for energy in the production of space heat. The model is used to simulate the behavior of poor and nonpoor households during a period of rising energy prices. This simulation illustrates the greater impact of rising prices on poor households.

......educational attainment, Hispanic ethnicity, household income, and home tenure...on the two persons in the household as well as the Hispanic ethnicity status of the head of household (assuming that the Hispanic ethnicity status of persons......

By product, transport of coal and coke and intermediate goods make the largest contribution to overall freight transport emissions associated with French householdconsumption. ... Finally, improving rail and inland water transportation infrastructure between northern European countries and France also serves the purpose of improving trade-relations and economic efficiency within Europe. ... per capita footprints were 1 ton CO2 equiv./yr in African countries to ?30ton CO2 equiv./yr in Luxembourg and the USA. ...

In this study, households’ decisions on reconstruction of damaged houses were modeled, using questionnaire data in Japan. Characteristics of households’ decisions were investigated using parameter estimation resu...

Figure on manufacturing production indexes and purchased energy consumption Figure on manufacturing production indexes and purchased energy consumption Source: Energy Information Administration and Federal Reserve Board. History of Shipments This chart presents indices of 14 years (1980-1994) of historical data of manufacturing production indexes and Purchased (Offsite-Produced) Energy consumption, using 1992 as the base year (1992 = 100). Indexing both energy consumption and production best illustrates the trends in output and consumption. Taken separately, these two indices track the relative growth rates within the specified industry. Taken together, they reveal trends in energy efficiency. For example, a steady increase in output, coupled with a decline in energy consumption, represents energy efficiency gains. Likewise, steadily rising energy consumption with a corresponding decline in output illustrates energy efficiency losses.

A study was carried out to develop a typology of urban metabolic (or resource consumption) profiles for 155 globally representative cities. Classification tree analysis was used to develop a model for determining how certain ...

This paper describes the theoretical background and results of a focus group study on determinants of energy related behaviour in Norwegian households. 70 Norwegians between 18 and 79 years of age participated in eight focus-groups in four Norwegian cities. The aim of the study was to identify behaviours that Norwegians consider relevant with respect to energy use, the main determinants of those behaviours, as well as barriers against and facilitators of energy efficiency. The most important behaviours from the participants' perspectives were heating, water heating, use of white ware and mobility. The main motivators named were minimising behavioural costs, value orientations, perceived consumer efficacy and social norms. The most important barriers were structural misfits, economic, effort, time consumption, low consumer efficacy and lack of relevant and trustworthy information. The most potent facilitators were economic incentives, gains in comfort, reduced effort, tailored practical information, individual feedback and legislative actions.

Sample records for household consumption profiles from the National Library of Energy Beta (NLEBeta)

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for discussions. This year's symposium is held at Peebles Hotel Hydro in the small town of Peebles (populationHouseholder Symposium on Numerical Linear Algebra June 17Â­21, 2002 Peebles Hotel Hydro, Scotland

A survey was conducted to determine occupant use of windows and mechanical ventilation devices; barriers that inhibit their use; satisfaction with indoor air quality (IAQ); and the relationship between these factors. A questionnaire was mailed to a stratified random sample of 4,972 single-family detached homes built in 2003, and 1,448 responses were received. A convenience sample of 230 houses known to have mechanical ventilation systems resulted in another 67 completed interviews. Some results are: (1) Many houses are under-ventilated: depending on season, only 10-50% of houses meet the standard recommendation of 0.35 air changes per hour. (2) Local exhaust fans are under-utilized. For instance, about 30% of households rarely or never use their bathroom fan. (3) More than 95% of households report that indoor air quality is ''very'' or ''somewhat'' acceptable, although about 1/3 of households also report dustiness, dry air, or stagnant or humid air. (4) Except households where people cook several hours per week, there is no evidence that households with significant indoor pollutant sources get more ventilation. (5) Except households containing asthmatics, there is no evidence that health issues motivate ventilation behavior. (6) Security and energy saving are the two main reasons people close windows or keep them closed.

Policy makers rely on transportation statistics, including data on personal travel behavior, to formulate strategic transportation policies, and to improve the safety and efficiency of the U.S. transportation system. Data on personal travel trends are needed to examine the reliability, efficiency, capacity, and flexibility of the Nation's transportation system to meet current demands and to accommodate future demand. These data are also needed to assess the feasibility and efficiency of alternative congestion-mitigating technologies (e.g., high-speed rail, magnetically levitated trains, and intelligent vehicle and highway systems); to evaluate the merits of alternative transportation investment programs; and to assess the energy-use and air-quality impacts of various policies. To address these data needs, the U.S. Department of Transportation (USDOT) initiated an effort in 1969 to collect detailed data on personal travel. The 1969 survey was the first Nationwide Personal Transportation Survey (NPTS). The survey was conducted again in 1977, 1983, 1990, 1995, and 2001. Data on daily travel were collected in 1969, 1977, 1983, 1990 and 1995. In 2001, the survey was renamed the National Household Travel Survey (NHTS) and it collected both daily and long-distance trips. The 2001 survey was sponsored by three USDOT agencies: Federal Highway Administration (FHWA), Bureau of Transportation Statistics (BTS), and National Highway Traffic Safety Administration (NHTSA). The primary objective of the survey was to collect trip-based data on the nature and characteristics of personal travel so that the relationships between the characteristics of personal travel and the demographics of the traveler can be established. Commercial and institutional travel were not part of the survey. Due to the survey's design, data in the NHTS survey series were not recommended for estimating travel statistics for categories smaller than the combination of Census division (e.g., New England, Middle Atlantic, and Pacific), MSA size, and the availability of rail. Extrapolating NHTS data within small geographic areas could risk developing and subsequently using unreliable estimates. For example, if a planning agency in City X of State Y estimates travel rates and other travel characteristics based on survey data collected from NHTS sample households that were located in City X of State Y, then the agency could risk developing and using unreliable estimates for their planning process. Typically, this limitation significantly increases as the size of an area decreases. That said, the NHTS contains a wealth of information that could allow statistical inferences about small geographic areas, with a pre-determined level of statistical certainty. The question then becomes whether a method can be developed that integrates the NHTS data and other data to estimate key travel characteristics for small geographic areas such as Census tract and transportation analysis zone, and whether this method can outperform other, competing methods.

Historical and projected world energy consumption information is displayed. The information is presented by region and fuel type, and includes a world total. Measurements are in quadrillion Btu. Sources of the information contained in the table are: (1) history--Energy Information Administration (EIA), International Energy Annual 1992, DOE/EIA-0219(92); (2) projections--EIA, World Energy Projections System, 1994. Country amounts include an adjustment to account for electricity trade. Regions or country groups are shown as follows: (1) Organization for Economic Cooperation and Development (OECD), US (not including US territories), which are included in other (ECD), Canada, Japan, OECD Europe, United Kingdom, France, Germany, Italy, Netherlands, other Europe, and other OECD; (2) Eurasia--China, former Soviet Union, eastern Europe; (3) rest of world--Organization of Petroleum Exporting Countries (OPEC) and other countries not included in any other group. Fuel types include oil, natural gas, coal, nuclear, and other. Other includes hydroelectricity, geothermal, solar, biomass, wind, and other renewable sources.

The changes in the patterns of energy use and expenditures by population group are analyzed by using the 1993 and 1997 Residential Energy Consumption Surveys. Historically, these patterns have differed among non-Hispanic White households, non-Hispanic Black households, and Hispanic households. Patterns of energy use and expenditures are influenced by geographic and metropolitan location, the composition of housing stock, economic and demographic status, and the composition of energy use by end-use category. As a consequence, as energy-related factors change across groups, patterns of energy use and expenditures also change. Over time, with changes in the composition of these factors by population group and their variable influences on energy use, the impact on energy use and expenditures has varied across these population groups.

Delivering Energy Efficiency to Middle Income Single Family Households Delivering Energy Efficiency to Middle Income Single Family Households Title Delivering Energy Efficiency to Middle Income Single Family Households Publication Type Report Year of Publication 2011 Authors Zimring, Mark, Merrian Borgeson, Ian M. Hoffman, Charles A. Goldman, Elizabeth Stuart, Annika Todd, and Megan A. Billingsley Pagination 102 Date Published 12/2011 Publisher LBNL City Berkeley Keywords electricity markets and policy group, energy analysis and environmental impacts department Abstract The question posed in this report is: How can programs motivate these middle income single family households to seek out more comprehensive energy upgrades, and empower them to do so? Research methods included interviews with more than 35 program administrators, policy makers, researchers, and other experts; case studies of programs, based on interviews with staff and a review of program materials and data; and analysis of relevant data sources and existing research on demographics, the financial status of Americans, and the characteristics of middle income American households. While there is no 'silver bullet' to help these households overcome the range of barriers they face, this report describes outreach strategies, innovative program designs, and financing tools that show promise in increasing the attractiveness and accessibility of energy efficiency for this group. These strategies and tools should be seen as models that are currently being honed to build our knowledge and capacity to deliver energy improvements to middle income households. However, the strategies described in this report are probably not sufficient, in the absence of robust policy frameworks, to deliver these improvements at scale. Instead, these strategies must be paired with enabling and complementary policies to reach their full potential.

All Reports & Publications All Reports & Publications Search By: Go Pick a date range: From: To: Go graph of U.S. electricity end use, as explained in the article text U.S. electricity sales have decreased in four of the past five years December 20, 2013 Gas furnace efficiency has large implications for residential natural gas use December 5, 2013 EIA publishes state fact sheets on residential energy consumption and characteristics August 19, 2013 All 48 related articles â€º ResidentialAvailable formats PDF Modeling Distributed Generation in the Buildings Sectors Released: August 29, 2013 This report focuses on how EIA models residential and commercial sector distributed generation, including combined heat and power, for the Annual Energy Outlook. State Fact Sheets on Household Energy Use

Air conditioning in nearly 100 million U.S. homes Air conditioning in nearly 100 million U.S. homes RECS 2009 - Release date: August 19, 2011 line chart:air conditioning in U.S. figure dataExcept in the temperate climate regions along the West coast, air conditioners (AC) are now standard equipment in most U.S. homes (Figure 1). As recently as 1993, only 68% of all occupied housing units had AC. The latest results from the 2009 Residential Energy Consumption Survey (RECS) show that 87 percent of U.S. households are now equipped with AC. This growth occurred among all housing types and in every Census region. Wider use has coincided with much improved energy efficiency standards for AC equipment, a population shift to hotter and more humid regions, and a housing boom during which average housing sizes increased.

Fact Sheet: Gas Prices and Oil Consumption Would Increase Without Fact Sheet: Gas Prices and Oil Consumption Would Increase Without Biofuels Fact Sheet: Gas Prices and Oil Consumption Would Increase Without Biofuels June 11, 2008 - 1:30pm Addthis Secretary of Energy Samuel W. Bodman and Secretary of Agriculture Edward T. Schafer sent a letter on June 11, 2008 to Senator Jeff Bingaman addressing a number of questions related to biofuels, food, and gasoline and diesel prices. Read the letter. Without Biofuels, Gas Prices Would Increase $.20 to $.35 per Gallon. The U.S. Department of Energy (DOE) estimates that gasoline prices would be between 20 cents to 35 cents per gallon higher without ethanol1, a first-generation biofuel. For a typical household, that means saving about $150 to $300 per year. For the U.S. overall, this saves gas expenditures of $28 billion to

Gas Prices and Oil Consumption Would Increase Without Gas Prices and Oil Consumption Would Increase Without Biofuels Fact Sheet: Gas Prices and Oil Consumption Would Increase Without Biofuels June 11, 2008 - 1:30pm Addthis Secretary of Energy Samuel W. Bodman and Secretary of Agriculture Edward T. Schafer sent a letter on June 11, 2008 to Senator Jeff Bingaman addressing a number of questions related to biofuels, food, and gasoline and diesel prices. Read the letter. Without Biofuels, Gas Prices Would Increase $.20 to $.35 per Gallon. The U.S. Department of Energy (DOE) estimates that gasoline prices would be between 20 cents to 35 cents per gallon higher without ethanol1, a first-generation biofuel. For a typical household, that means saving about $150 to $300 per year. For the U.S. overall, this saves gas expenditures of $28 billion to

Sample records for household consumption profiles from the National Library of Energy Beta (NLEBeta)

Note: This page contains sample records for the topic "household consumption profiles" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
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An overview of options and potential barriers and risks for reducing the energy consumption, peak demand, and emissions for seven key energy consuming residential products (refrigerator-freezers, dishwashers, clothes washers, clothes dryers, electric ovens, gas ovens and microwave ovens) is presented. The paper primarily concentrates on the potential energy savings from the use of advanced technologies in appliances for the U.S. market. The significance and usefulness of each technology was evaluated in order to prioritize the R&D needs to improve energy efficiency of appliances in view of energy savings, cost, and complexity. The paper provides a snapshot of the future R&D needs for each of the technologies along with the associated barriers. Although significant energy savings may be achieved, one of the major barriers in most cases is high first cost. One way of addressing this issue and promoting the introduction of new technologies is to level the playing field for all manufacturers by establishing Minimum Energy Performance Standards (MEPS) which are not cost prohibitive and promoting energy efficient products through incentives to both manufacturers and consumers.

Water Related Energy Use in Households and Cities - an Australian Water Related Energy Use in Households and Cities - an Australian Perspective Speaker(s): Steven Kenway Date: May 12, 2011 - 12:00pm Location: 90-3122 Seminar Host/Point of Contact: Anita Estner James McMahon This presentation covers the content of recent journal papers and reports focused on the water-energy nexus and the related theory of urban metabolism. This includes (i) a review of the water-energy nexus focused on cities (ii) quantifying water-related energy in cities (iii) modeling household water-related energy use including key factors, sensitivity and uncertainty analysis, and (iv) relevance and implications of the urban metabolism theoretical framework. Steven's work focuses on understanding the indirect connections between urban water management, energy use and

This paper presents the findings of an exploratory study based on a survey of 1,537 households in Spain. The questionnaire included 23 key questions regarding the number of appliances in use, previous appliances lifetimes, reasons for buying each new appliance and end-of-life handling of discarded appliances. The distribution of the households along a number of relevant factors was analysed and a prototypical household was identified. A non-parametric analysis of the duration of each type of appliance has also been carried out and it was found that television sets are the most durable of the appliances considered. Survival rates for irons fall more rapidly than for microwaves. Moreover, television sets are the most durable of the appliances considered. Replacement rates of personal computers rapidly increase after approximately six to eight years. Finally, a statistical analysis of the respondents motivations for recycling the appliances considered in this study was carried out.

This paper describes the performance test results of an automatic icemaker refrigerator under various modes of icemaker operation. The tests were conducted on a 20-ft{sup 3} (0.566-m{sup 3}) household refrigerator that had a single forced convection evaporator and was charged with R-12. The focus of the research was to ascertain the effect of icemaker operation on the refrigerator`s daily energy consumption. Thus, three different types of tests were conducted, depending upon the icemaker`s operating mode. In the first test type, the baseline, the automatic icemaker was turned off and no ice was made. In the second test type, the ice-making mode (test A), the icemaker was turned on and ice was continuously made. Compared to the baseline, additional power was intermittently consumed by a mold heater that melts the ice cubes` interface with the tray, a solenoid valve that supplies water to the icemaker tray, and a motor that rotates the ejector blades to press the crescent-shaped ice cubes out of the mold and unload them into an ice bin. In the third test type, the failure mode (test B), the water supply was manually disconnected but the icemaker was left turned on. Even though no ice was made, additional power was still consumed by the mold heater, the solenoid valve, and the motorized ejector. In tests A and B, the energy consumed by the icemaker`s components increases the cooling load, which raises the compressor power consumption. The present study shows that at the AHAM-specified test conditions, uninterrupted icemaking increased the daily energy consumption by 22.5% to 27.2%.

energy data used in this report do not reflect adjustments for losses in electricity generation or transmission. energy data used in this report do not reflect adjustments for losses in electricity generation or transmission. 1 The manufacturing sector is composed of establishments classified in Standard Industrial Classification 20 through 39 of the U.S. economy as defined 2 by the Office of Management and Budget. The manufacturing sector is a part of the industrial sector, which also includes mining; construction; and agriculture, forestry, and fishing. The EIA also conducts energy consumption surveys in the residential, commercial buildings, and residential transportation sectors: the Residential Energy 3 Consumption Survey (RECS); the Commercial Buildings Energy Consumption Survey (CBECS); and, until recently, the Residential Transportation Energy Consumption Survey (RTECS).

We derive new estimates of total wealth, the returns on total wealth, and the wealth effect on consumption. We estimate the prices of aggregate risk from bond yields and stock returns using a no-arbitrage model. Using these ...

Trends in the marketplace show that urban dwellers are increasingly supporting locally produced foods. This thesis argues for an architecture that responds to our cultures consumptive behaviors. Addressing the effects of ...

The MIT community has embarked on an initiative to the reduce energy consumption and in accordance with the Kyoto Protocol. This thesis seeks to further expand our understanding of how the MIT campus consumes energy and ...

Optimal consumption strategies under model uncertainty Christian Burgert, Ludger R of finding optimal consumption strategies in an incomplete semimartingale market model under model uncertainty. The quality of a consumption strategy is measured by not only one probability measure

Understanding the key drivers behind China’s mass consumption of raw materials is thus crucial for developing sustainable resource management and providing valuable insights into how other emerging economies may be aiming to accomplish a low resource-dependent future. ... Of these two influencing factors, urbanization is the predominant driving force behind increasing RMC, characterized by the rapid increase in urbanization-related investment, notably in the construction sector (e.g., infrastructure, real estate), and rises in urban householdconsumption. ... Environmental sustainability can only be achieved by timely technol. ...

This report provides estimates on energy consumption in the manufacturing sector of the US economy. These estimates are based on data from the 1991 Manufacturing Energy Consumption Survey (MECS). This survey--administered by the Energy End Use and Integrated Statistics Division, Office of Energy Markets and End Use, Energy Information Administration (EIA)--is the most comprehensive source of national-level data on energy-related information for the manufacturing industries.

The implementation of the principles of sustainable development requires both using potentialities in saving resources and cutting down emissions (efficiency strategies) as well as more conscious patterns of behaviour of the actors involved (sufficiency strategies). Starting from the current situation of annual CO2 emissions of about 10 t and a sustainability goal of 1â??2 t CO2 emissions per inhabitant and year, the question arises in how far households can contribute to achieve this goal. Therefore, in this paper, the environmental impacts of the energy demand of German households will be evaluated by means of describing its status quo and there from deriving saving potentials.

Solid waste management (SWM) is a multidimensional challenge faced by urban authorities, especially in developing countries like Bangladesh. We investigated per capita waste generation by residents, its composition, and the households' attitudes towards waste management at Rahman Nagar Residential Area, Chittagong, Bangladesh. The study involved a structured questionnaire and encompassed 75 households from five different socioeconomic groups (SEGs): low (LSEG), lower middle (LMSEG), middle (MSEG), upper middle (UMSEG) and high (HSEG). Wastes, collected from all of the groups of households, were segregated and weighed. Waste generation was 1.3 kg/household/day and 0.25 kg/person/day. Household solid waste (HSW) was comprised of nine categories of wastes with vegetable/food waste being the largest component (62%). Vegetable/food waste generation increased from the HSEG (47%) to the LSEG (88%). By weight, 66% of the waste was compostable in nature. The generation of HSW was positively correlated with family size (r{sub xy} = 0.236, p < 0.05), education level (r{sub xy} = 0.244, p < 0.05) and monthly income (r{sub xy} = 0.671, p < 0.01) of the households. Municipal authorities are usually the responsible agencies for solid waste collection and disposal, but the magnitude of the problem is well beyond the ability of any municipal government to tackle. Hence dwellers were found to take the service from the local waste management initiative. Of the respondents, an impressive 44% were willing to pay US$0.3 to US$0.4 per month to waste collectors and it is recommended that service charge be based on the volume of waste generated by households. Almost a quarter (22.7%) of the respondents preferred 12-1 pm as the time period for their waste to be collected. This study adequately shows that household solid waste can be converted from burden to resource through segregation at the source, since people are aware of their role in this direction provided a mechanism to assist them in this pursuit exists and the burden is distributed according to the amount of waste generated.

Sample records for household consumption profiles from the National Library of Energy Beta (NLEBeta)

Note: This page contains sample records for the topic "household consumption profiles" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.

Sample records for household consumption profiles from the National Library of Energy Beta (NLEBeta)

Note: This page contains sample records for the topic "household consumption profiles" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.

the average household size for Hispanic respondents isper year, while households of black and Hispanic respondentsHispanic” versus “settled” and native born residents. Vehicle ownership is highly correlated with mode choice as households

Home > Households, Buildings & Industry > Commercial Buildings Energy Consumption Survey (CBECS) > 2003 Detailed Tables > What is an RSE? What is an RSE? The estimates in the Commercial Buildings Energy Consumption Survey (CBECS) are based on data reported by representatives of a statistically-designed subset of the entire commercial building population in the United States, or a "sample". Consequently, the estimates differ from the true population values. However, the sample design permits us to estimate the sampling error in each value. It is important to understand: CBECS estimates should not be considered as finite point estimates, but as estimates with some associated error in each direction. The standard error is a measure of the reliability or precision of the survey statistic. The value for the standard error can be used to construct confidence intervals and to perform hypothesis tests by standard statistical methods. Relative Standard Error (RSE) is defined as the standard error (square root of the variance) of a survey estimate, divided by the survey estimate and multiplied by 100.

energy-using devices in the average U.S. household that used over 4,700 kWh of electricity, natural gas.46]. The cost of these devices was also statistically significant. Keywords: electricity use; energy efficiency the Canadian Industrial Energy End Use Data and Analysis (CIEEDAC) for their financial support made possible

In fact ours is not the first attempt to use the household production function technique empirically to estimate the ... climate and the impact of climate change on households. But our analysis uses repeated cros...

ABSTRACT This paper introduces a methodology for estimation of energy consumption in peripherals such as audio and video devices. Peripherals can be responsible for significant amount of the energy consumption in current embedded systems. We introduce a cycle- accurate energy simulator and profiler capable

SUPERB Indoor environment d-limonene a b s t r a c t The use of household cleaning products and air, frequencies of use of eight types of household cleaning products and air fresheners and the performance. Introduction Household care products, such as cleaning products and air fresheners, are frequently used

above, Biggs and Akcelik (1985) proposed a model of the following form: f = fsito + &Pr + z[apr)o o (5) where, Po = total drag power P, = inertia power a = instantaneous acceleration 8, = fuel consumption per unit power 8, = fuel consumption per... that is additional to S, P, . This component is expressed as SzaP, , where &z is considered to be a secondary efficiency parameter that relates fuel to the product of inertia power and acceleration rate, for positive accelerations. This term allows for the effects...

...Transit and Energy Consumption In a recent issue...D.C. 20418 The Diesel's Advantages It...p. 517). The diesel car, while it has...Other types of engine can be made to meet...catalysts by using leaded fuel because it is 3 to...politically unpopular. The diesel car requires no add-on...

Abstract Assessing grid developments the spatial distribution of the electricity consumption is important. In Denmark the electricity grid consists of transmission – and local distribution grids with different voltages that are connected via transformer stations each covering a local area with between 10.000 and 100.000 customers. Data for the hourly electricity consumption at transformer stations shows that the profile of consumption differs considerably between local areas, and this is partly due to a different weight of categories of customers in the different areas. Categories of customers have quite distinct consumptionprofiles and contribute quite differently to the aggregated load profile. In forecasts, demand by categories of customers is expected to develop differently implying that both the level and the profile of consumption at each transformer stations are expected to change differently. Still, in the previous planning of the transmission grid in Denmark specific local conditions have not been considered. As a first step towards differentiated local load forecasts, the paper presents a new model for long term projections of consumption in local areas and illustrates a first use of the model related to the transmission grid planning by the Danish TSO Energinet.dk. The model is a distribution system that distributes hourly consumption in an aggregated area to hourly consumption at each transformer station. Using econometrics, the model is estimated on national statistics for the hourly consumption by categories of customers and data for the hourly consumption at each transformer station for the years 2009–2011. Applying the model for load forecasts, a major conclusion is that different transformer stations will experience different changes both in the level - and in the hourly profile of load.

Sample records for household consumption profiles from the National Library of Energy Beta (NLEBeta)

Note: This page contains sample records for the topic "household consumption profiles" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
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This paper provides new evidence of consumers’ reaction to an anticipated sizable change in income. Until FY2002, Japanese public employees received predictable large bonus payments three times a fiscal year (in June, December, and March), but the March bonus was abolished in FY2003. We compare the seasonal patterns of public employees’ expenditure before and after the reform of the bonus payment schedule. Contrary to the prediction of the life cycle/permanent income hypothesis (LC/PIH), we find evidence that monthly patterns of household expenditure were significantly affected by the anticipated large change in income pattern. However, at closer inspection, this excess sensitivity of expenditure is observed only for expenditure subcategories of some durability, i.e., durables and semi-durables. Thus, while the LC/PIH does not appear to hold for expenditure (which we observe here), it may still hold for consumption.

This next slide shows what fuels are used in the residential market. When a This next slide shows what fuels are used in the residential market. When a energy supply event happens, particularly severe winter weather, it is this sector that the government becomes most concerned about. As you can see, natural gas is very important to the residential sector not only in DC, MD and VA but in the United States as well. DC residents use more natural gas for home heating than do MD and VA. While residents use heating oil in all three states, this fuel plays an important role in MD and VA. Note: kerosene is included in the distillate category because it is an important fuel to rural households in MD and VA. MD and VA rely more on electricity than DC. Both MD and VA use propane as well. While there are some similarities in this chart, it is interesting to note

Mentee Profile Mentee Profile The information you provide on this form will assist us in providing you with a list of prospective mentor from which to choose the most appropriate match. Once you've completed the form, please email it to doementoringprogram@hq.doe.gov . Thank you for your interest in the DOE Mentoring Program. Name (last/first): Phone Number: Job Title/Series/Grade: Organization (indicate HQ or field - complete address): Email Address: Are you a Veteran? If yes, do want a veteran mentee? If yes, which branch of the service? Are you student or intern? Do you have a preference on mentor? For example, male, female, particular career field, specific person or other? If so, what or who? Do you want a mentor in your career field? What are your career goals?

Mentor Profile Mentor Profile The information you provide on this form will assist us in providing you with a list of prospective mentee from which to choose the most appropriate match. Once you've completed the form, please email it to doementoringprogram@hq.doe.gov . Thank you for your interest in the DOE Mentoring Program. Name (last/first): Phone Number: Job Title/Series/Grade: Organization (indicate HQ or field - complete address): Email Address: Are you a Veteran? If yes, do want a veteran mentee? If yes, which branch of the service? Do you want a student or intern mentee? Do you have a preference on mentee? For example, male, female, particular career field or other? If so, what or state name of pre selected mentee? Do you want a mentee in your career field? What are your hobbies?

8) 8) Dataset Summary Description The UK Department of Energy and Climate Change (DECC) releases annual statistics on domestic and non-domestic electricity and gas consumption (and number of meters) at the Middle Layer Super Output Authority (MLSOA) and Intermediate Geography Zone (IGZ) level (there are over 950 of these subregions throughout England, Scotland and Wales). Both MLSOAs (England and Wales) and IGZs (Scotland) include a minimum of approximately 2,000 households. The electricity consumption data data is split by ordinary electricity and economy7 electricity usage. All data in this set are classified as UK National Statistics. Related socio-economic data for MLSOA and IGZ levels can be accessed: http://decc.gov.uk/assets/decc/Statistics/regional/mlsoa2008/181-mlsoa-i...

The U.S. DOE Residential Lighting End-Use Consumption Study is an initiative of the U.S. Department of Energy’s (DOE’s) Solid-State Lighting Program that aims to improve the understanding of lighting energy usage in residential dwellings. The study has developed a regional estimation framework within a national sample design that allows for the estimation of lamp usage and energy consumption 1) nationally and by region of the United States, 2) by certain household characteristics, 3) by location within the home, 4) by certain lamp characteristics, and 5) by certain categorical cross-classifications (e.g., by dwelling type AND lamp type or fixture type AND control type).

During 1992, the Energy Information Administration (EIA) conducted a user-needs study for the 1993 Residential Energy Consumption Survey (RECS). Every 3 years, the RECS collects information on energy consumption and expenditures for various classes of households and residential buildings. The RECS is the only source of such information within EIA, and one of only a few sources of such information anywhere. EIA sent letters to more than 750 persons, received responses from 56, and held 15 meetings with users. Written responses were also solicited by notices published in the April 14, 1992 Federal Register and in several energy-related publications. To ensure that the 1993 RECS meets current information needs, EIA made a specific effort to get input from policy makers and persons needing data for forecasting efforts. These particular needs relate mainly to development of the National Energy Modeling System and new energy legislation being considered at the time of the user needs survey.

B B : E S T I M AT I O N M E T H O D O L O G I E S APPENDIX B A P P E N D I X B ESTIMATION METHODOLOGIES INTRODUCTION The National Household Travel Survey (NHTS) is the nation's inventory of local and long distance travel, according to the U.S. Department of Transportation. Between April 2001 and May 2002, roughly 26 thousand households 41 were interviewed about their travel, based on the use of over 53 thousand vehicles. Using confidential data collected during those interviews, coupled with EIA's retail fuel prices, external data sources of test 42 fuel economy, and internal procedures for modifying test fuel economy to on-road, in-use fuel economy, EIA has extended this inventory to include the energy used for travel, thereby continuing a data series that was discontinued by EIA in 1994. This appendix presents the methods used for each eligible sampled

The purpose of this research is to estimate individual fuel prices within the residential sector. The data from four US Department of Energy, Energy Information Administration, residential energy consumption surveys were used to estimate the models. For a number of important fuel types - fuel oil, natural gas, and liquefied petroleum gas - the estimation presents a problem because these fuels are not used by all households. Estimates obtained by using only data in which observed fuel prices are present would be biased. A correction for this self-selection bias is needed for estimating prices of these fuels. A literature search identified no past studies on application of the selectivity model for estimating prices of residential fuel oil/kerosine, natural gas, and liquefied petroleum gas. This report describes selectivity models that utilize the Dubin/McFadden correction method for estimating prices of residential fuel oil/kerosine, natural gas, and liquefied petroleum gas in the Northeast, Midwest, South, and West census regions. Statistically significant explanatory variables are identified and discussed in each of the models. This new application of the selectivity model should be of interest to energy policy makers, researchers, and academicians.

This study was carried out at the laboratory scale (approximately 15 l) and using real baled waste of industrial dimensions (about 1 m3), in order to assess the long-term behaviour of baled household waste. The laboratory assays were carried out with real household waste which was fractioned on site, reconstituted in the laboratory and then compacted into 15 l airtight containers (unless stated otherwise). These containers were incubated under different experimental conditions at a constant temperature (28°C). Three assays were conducted over 34 months and two others over 27 months. For the assays incubated in conditions simulating those of real baled waste (confined medium, with no aeration or water flow), a very low microbial activity was observed. The assay incubated in the same conditions but with slight aeration during the first three months in order to simulate imperfectly airtight wrapping, revealed biodegradation which started in a significant manner after 800 days of incubation. The evolution of two real wrapped bales each containing 900 kg of household waste was monitored over 8 months. These bales were produced industrially, one in July 97 and the other in July 98 at the incinerator plant at Agde (France). The bales were then stored outside at the laboratory location and their evolution was monitored mainly by biogas analysis and temperature measurement. No methane formation was observed, revealing the absence of anaerobic biodegradation, thus confirming the laboratory assays.

Energy Information Administration/Manufacturing Consumption of Energy 1994 Energy Information Administration/Manufacturing Consumption of Energy 1994 Introduction The market for natural gas has been changing for quite some time. As part of natural gas restructuring, gas pipelines were opened to multiple users. Manufacturers or their representatives could go directly to the wellhead to purchase their natural gas, arrange the transportation, and have the natural gas delivered either by the local distribution company or directly through a connecting pipeline. More recently, the electricity markets have been undergoing change. When Congress passed the Energy Policy Act of 1992, requirements were included not only to open access to the ownership of electricity generation, but also to open access to the transmission lines so that wholesale trade in electricity would be possible. Now several States, including California and

Manufacturing Manufacturing Energy Consumption Survey Forms Form EIA-846A (4-6-95) U.S. Department of Commerce Bureau of the Census Acting as Collecting and Compiling Agent For 1994 MANUFACTURING ENERGY CONSUMPTION SURVEY Public reporting burden for this collection of information is estimated to average 9 hours per response, including the time of reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden, to the Energy Information Administration, Office of Statistical Standards, EI-73, 1707 H-Street, NW, Washington, DC 20585; and to the Office of Information and Regulatory Affairs, Office of

2(94) 2(94) Distribution Category UC-950 Manufacturing Consumption of Energy 1994 December 1997 Energy Information Administration Office of Energy Markets and End Use U.S. Department of Energy Washington, DC 20585 This report was prepared by the Energy Information Administration, the independent statistical and analytical agency within the U.S. Department of Energy. The information contained herein should be attributed to the Energy Information Administration and should not be construed as advocating or reflecting any policy position of the Department of Energy or any other organization. ii Energy Information Administration/Manufacturing Consumption of Energy 1994 Contacts This publication was prepared by the Energy Information Administration (EIA) under the general direction of W. Calvin

Sample records for household consumption profiles from the National Library of Energy Beta (NLEBeta)

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This thesis consists of three essays on aggregate and individual consumption fluctuations. Chapter 1 develops a quantitative model to explore aggregate and individual consumption dynamics when the income process exhibits ...

Reduced Energy Consumption for Melting in Foundries Ph.D. Thesis by SÃ¸ren Skov-Hansen Supervisor-melted, and hence reduce the energy consumption for melting in foundries. Traditional gating systems are known

Variability of Behaviour in Electricity Load Profile Clustering; Who Does Things at the Same Time://ima.ac.uk/dent 2 The James Hutton Institute, Aberdeen, UK Abstract. UK electricity market changes provide opportunities to alter households' electricity usage patterns for the benefit of the overall elec- tricity

ConsumptionConsumption 2010 Natural Gas Year-In-Review 2009 This is a special report that provides an overview of the natural gas industry and markets in 2009 with special focus on the first complete set of supply and disposition data for 2009 from the Energy Information Administration. Topics discussed include natural gas end-use consumption trends, offshore and onshore production, imports and exports of pipeline and liquefied natural gas, and above-average storage inventories. Categories: Prices, Production, Consumption, Imports/Exports & Pipelines, Storage (Released, 7/9/2010, Html format) Trends in U.S. Residential Natural Gas Consumption This report presents an analysis of residential natural gas consumption trends in the United States through 2009 and analyzes consumption trends for the United States as a whole (1990 through 2009) and for each Census Division (1998 through 2009). It examines a long-term downward per-customer consumption trend and analyzes whether this trend persists across Census Divisions. The report also examines some of the factors that have contributed to the decline in per-customer consumption. To provide a more meaningful measure of per-customer consumption, EIA adjusted consumption data presented in the report for weather. Categories: Consumption (Released, 6/23/2010, pdf format)

Ethanol Consumption by Rat Dams During Gestation, Lactation and Weaning Increases Ethanol examined effects of ethanol consumption in rat dams during gestation, lactation, and weaning on voluntary ethanol consumption by their adolescent young. We found that exposure to an ethanol-ingesting dam

Consumption Oriented Free Capitalism Qiudong Wang An economic system is a framework, under which people are organized to produce consumption-goods and to consume the produced. Concerning economic of consumption, which in turn not only hindered further improvement of overall productivity, but also threatened

STATE OF CALIFORNIA FAN POWER CONSUMPTION CEC-MECH-4C (Revised 08/09) CALIFORNIA ENERGY COMMISSION FAN POWER CONSUMPTION MECH-4C PROJECT NAME: DATE: NOTE: Provide one copy of this worksheet for each Systems or Variable Air Volume (VAV) Systems when using the Prescriptive Approach. See Power Consumption

Energy Consumption of Personal Computing Including Portable Communication Devices Pavel Somavat1 consumption, questions are being asked about the energy contribution of computing equipment. Al- though studies have documented the share of energy consumption by this type of equipment over the years, research

Hard Drive Power Consumption Uncovered Computer Laboratory Digital Technology Group Anthony Hylick, Andrew Rice, Brian Jones, Ripduman Sohan Motivation Attempts to reduce power consumption have mainly of power consumption and identify the need for a more expressive API between the OS and hardware devices

Sample records for household consumption profiles from the National Library of Energy Beta (NLEBeta)

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...May 2004 research-article The food consumption of the world's seabirds M. de L...provisional estimate of their annual food consumption. Knowing the body mass and energy density...equations to estimate daily and hence annual consumption of a seabird. Using this approach...

Optimal Consumption Choice with Intertemporal Substitution y By Peter Bank and Frank Riedel z consumption plans are established under arbitrary convex portfolio constraints, including both complete of the underlying stochastics, optimal consumption occurs at rates, in gulps, or in a singular way. y Support

Per Capita Consumption 73 The NMFS calculation of per capita consumption is based to estimate per capita consumption. Data for the model are derived primarily from second- ary sources effect on the resulting calculation. U.S. per capita consumption of fish and shellfish was 16.5 pounds

Per Capita Consumption 73 The NMFS calculation of per capita consumption is based to estimate per capita consumption. Data for the model are derived primarily from second- ary sources effect on the resulting calculation. U.S. per capita consumption of fish and shellfish was 16.0 pounds

Per Capita Consumption 73 The NMFS calculation of per capita consumption is based to estimate per capita consumption. Data for the model are derived primarily from second- ary sources a significant effect on the resulting calculation. U.S. per capita consumption of fish and shellfish was 15

Per Capita Consumption 73 The NMFS calculation of per capita consumption is based to estimate per capita consumption. Data for the model are derived primarily from second- ary sources effect on the resulting calculation. U.S. per capita consumption of fish and shellfish was 16.3 pounds

Per Capita Consumption 84 The NMFS calculation of per capita consumption is based to estimate per capita consumption. Data for the model are derived primarily from second- ary sources effect on the resulting calculation. U.S. per capita consumption of fish and shellfish was 16.3 pounds

Indoor Secondary Pollutants from Household Product Emissions in the Indoor Secondary Pollutants from Household Product Emissions in the Presence of Ozone: A Bench-Scale Chamber Study Title Indoor Secondary Pollutants from Household Product Emissions in the Presence of Ozone: A Bench-Scale Chamber Study Publication Type Journal Article LBNL Report Number LBNL-58785 Year of Publication 2006 Authors Destaillats, Hugo, Melissa M. Lunden, Brett C. Singer, Beverly K. Coleman, Alfred T. Hodgson, Charles J. Weschler, and William W. Nazaroff Journal Environmental Science and Technology Volume 40 Start Page Chapter Pagination 4421-4428 Abstract Ozone-driven chemistry is a major source of indoor secondary pollutants of health concern. This study investigates secondary air pollutants formed from reactions between constituents of household products and ozone. Gas-phase product emissions were introduced along with ozone at constant rates into a 198-L Teflon-lined reaction chamber. Gas-phase concentrations of reactive terpenoids and oxidation products were measured. Formaldehyde was a predominant oxidation byproduct for the three studied products, with yields under most conditions of 20-30% with respect to ozone consumed. Acetaldehyde, acetone, glycolaldehyde, formic acid and acetic acid were each also detected for two or three of the products. Immediately upon mixing of reactants, a scanning mobility particle sizer detected particle nucleation events that were followed by a significant degree of ultrafine particle growth. The production of secondary gaseous pollutants and particles depended primarily on the ozone level and was influenced by other parameters such as the air-exchange rate. Hydroxyl radical concentrations in the range 0.04-200 Ã— 105 molecules cm-3 were measured. OH concentrations were observed to vary strongly with residual ozone level in the chamber, which was in the range 1 - 25 ppb, as is consistent with expectations from a simplified kinetic model. In a separate test, we exposed the dry residue of two products to ozone in the chamber and observed the formation of gas-phase and particle-phase secondary oxidation products

Due to industry concerns about the successful employment of hydrofluorocarbon-immiscible hydrocarbon oils in refrigeration systems, enhanced naphthenic refrigeration oils have been developed. These products have been designed to be more dispersible with hydrofluorocarbon (HFC) refrigerants, such as R-134a, in order to facilitate lubricant return to the compressor and to ensure proper energy efficiency of the system. Bench tests and system performance evaluations indicate the feasibility of these oils for use in household refrigeration applications. Results of these evaluations are compared with those obtained with polyol esters and typical naphthenic mineral oils employed in chlorofluorocarbon (CFC) and hydrochlorofluorocarbon (HCFC) refrigeration applications.

Sample records for household consumption profiles from the National Library of Energy Beta (NLEBeta)

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The objectives of this study are to determine effects of household members' characteristics, financial resources, and attitude ... Subsamples of White respondents, Black respondents, and Hispanic respondents were...

This report documents the travel behavior and transportation fuel use of minority and poor households in the US, using information from numerous national-level sources. The resulting data base reveals distinctive patterns of household vehicle availability and use, travel, and fuel use and enables us to relate observed differences between population groups to differences in their demographic characteristics and in the attributes of their household vehicles. When income and residence location are controlled, black (and to a lesser extent, Hispanic and poor) households have fewer vehicles regularly available than do comparable white or nonpoor households; moreover, these vehicles are older and larger and thus have significantly lower fuel economy. The net result is that average black, Hispanic, and poor households travel fewer miles per year but use more fuel than do average white and nonpoor households. Certain other findings - notably, that of significant racial differences in vehicle availability and use by low-income households - challenge the conventional wisdom that such racial variations arise solely because of differences in income and residence location. Results of the study suggest important differences - primarily in the yearly fluctuation of income - between black and white low-income households even when residence location is controlled. These variables are not captured by cross-sectional data sets (either the national surveys used in our analysis or the local data sets that are widely used for urban transportation planning).

Abstract This paper quantitatively evaluates consumers' willingness to pay for hybrid vehicles by estimating the demand of hybrid vehicles in the U.S. market. Using micro-level data on consumer purchases of hybrid and non-hybrid vehicles from National Household Travel Survey 2009, this paper formulates a mixed logit model of consumers' vehicle choices. Parameter estimates are then used to evaluate consumers' willingness to pay for hybrids. Results suggest that households' willingness to pay for hybrids ranges from $963 to $1718 for different income groups, which is significantly lower than the average price premium (over $5000) of hybrid vehicles, even when taking the fuel costs savings of hybrid vehicles into consideration. The differences reveal that although the market has shown increasing interest in hybrid vehicles, consumers' valuation of the hybrid feature is still not high enough to compensate for the price premium when they make new purchases. Policy simulations are conducted to examine the effects of raising federal tax incentives on the purchase of hybrid vehicles.

...specific behavioral changes, such as weatherization investments, to be adopted by US households...the United States switch to the latter metric. Demand-side policy responses to climate...survey, we frequently use US rather than metric units in the text and figures. As shown...

A24. A24. Total Inputs of Energy for Heat, Power, and Electricity Generation by Program Sponsorship, Industry Group, Selected Industries, and Type of Energy- Management Program, 1994: Part 1 (Estimates in Trillion Btu) See footnotes at end of table. Energy Information Administration/Manufacturing Consumption of Energy 1994 285 SIC Management Any Type of Sponsored Self-Sponsored Sponsored Sponsored Code Industry Group and Industry Program Sponsorship Involvement Involvement Involvement Involvement a No Energy Electric Utility Government Third Party Type of Sponsorship of Management Programs (1992 through 1994) RSE Row Factors Federal, State, or Local RSE Column Factors: 0.7 1.1 1.0 0.7 1.9 0.9 20-39 ALL INDUSTRY GROUPS Participation in One or More of the Following Types of Programs . .

3 3 Energy Information Administration/Manufacturing Consumption of Energy 1994 Glossary Anthracite: A hard, black, lustrous coal containing a high percentage of fixed carbon and a low percentage of volatile matter. Often referred to as hard coal. Barrel: A volumetric unit of measure equivalent to 42 U.S. gallons. Biomass: Organic nonfossil material of biological origin constituting a renewable energy source. Bituminous Coal: A dense, black coal, often with well-defined bands of bright and dull material, with a moisture content usually less than 20 percent. Often referred to as soft coal. It is the most common coal. Blast Furnace: A shaft furnace in which solid fuel (coke) is burned with an air blast to smelt ore in a continuous operation. Blast Furnace Gas: The waste combustible gas generated in a blast furnace when iron ore is being reduced with coke to

Manufacturing Manufacturing Sector Overview 1991-1994 Energy Information Administration/Manufacturing Consumption of Energy 1994 xiii Why Do We Investigate Energy Use in the Manufacturing Sector? What Data Do EIA Use To Investigate Energy Use in the Manufacturing Sector? In 1991, output in the manufactur- ing sector fell as the country went into a recession. After 1991, however, output increased as the country slowly came out of the recession. Between 1991 and 1994, manufacturers, especially manu- facturers of durable goods such as steel and glass, experienced strong growth. The industrial production index for durable goods during the period increased by 21 percent. Real gross domestic product for durable goods increased a corre- sponding 16 percent. The growth of nondurables was not as strong-- the production index increased by only 9 percent during this time period.

Survey Design, Survey Design, Implementation, and Estimates 411 Energy Information Administration/Manufacturing Consumption of Energy 1994 Overview of Changes from Previous Surveys Sample Design. The MECS has increased its sample size by roughly 40 percent since the 1991 survey, increasing the designed sample size from 16,054 establishments to 22,922. This increase in size and change in sampling criteria required a departure from using the Annual Survey of Manufactures (ASM) as the MECS sampling frame. For 1994, establishments were selected directly from the 1992 Census of Manufactures (CM) mail file, updated by 1993 ASM. Sample Frame Coverage. The coverage in the 1994 MECS is 98 percent of the manufacturing population as measured in total payroll. The sampling process itself provided that level of coverage, and no special adjustments were

Sample records for household consumption profiles from the National Library of Energy Beta (NLEBeta)

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ConsumptionConsumptionConsumption by End Use U.S. and State consumption by lease and plant, pipeline, and delivered to consumers by sector (monthly, annual). Number of Consumers Number of sales and transported consumers for residential, commercial, and industrial sectors by State (monthly, annual). State Shares of U.S. Deliveries By sector and total consumption (annual). Delivered for the Account of Others Commercial, industrial and electric utility deliveries; percentage of total deliveries by State (annual). Heat Content of Natural Gas Consumed Btu per cubic foot of natural gas delivered to consumers by State (annual) and other components of consumption for U.S. (annual). Natural Gas Weekly Update Analysis of current price, supply, and storage data; and a weather snapshot.

Several data can be presented as interval curves where ... particular, this representation is well adapted for load profiles, which depict the electricity consumption of a class of customers. Electricity load pro...

Presents a summary of the nation’s renewable energy consumption in 2010 along with detailed historical data on renewable energy consumption by energy source and end-use sector. Data presented also includes renewable energy consumption for electricity generation and for non-electric use by energy source, and net summer capacity and net generation by energy source and state. The report covers the period from 2006 through 2010.